Search results for: healthcare analytics

Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

Procedia PDF Downloads 156

Authors: Rishi Agarwal

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Digital twins are emerging as a strong technology used to imitate and monitor physical objects digitally in real time across sectors. It is not only dealing with the digital space, but it is also actuating responses in the physical space in response to the digital space processing like storage, modeling, learning, simulation, and prediction. This paper explores the application of digital twins for enhancing physical security in retail stores. The retail sector still relies on outdated physical security practices like manual monitoring and metal detectors, which are insufficient for modern needs. There is a lack of real-time data and system integration, leading to ineffective emergency response and preventative measures. As retail automation increases, new digital frameworks must control safety without human intervention. To address this, the paper proposes implementing an intelligent digital twin framework. This collects diverse data streams from in-store sensors, surveillance, external sources, and customer devices and then Advanced analytics and simulations enable real-time monitoring, incident prediction, automated emergency procedures, and stakeholder coordination. Overall, the digital twin improves physical security through automation, adaptability, and comprehensive data sharing. The paper also analyzes the pros and cons of implementation of this technology through an Emerging Technology Analysis Canvas that analyzes different aspects of this technology through both narrow and wide lenses to help decision makers in their decision of implementing this technology. On a broader scale, this showcases the value of digital twins in transforming legacy systems across sectors and how data sharing can create a safer world for both retail store customers and owners.

Keywords: digital twin, retail store safety, digital twin in retail, digital twin for physical safety

Procedia PDF Downloads 72

Authors: Ilham Zaidi, P. Sankara Sarma, Quazi Taufique Ahmed, V. Raman Kutty, Khalid Umer Khayyam, Gurpreet Singh, Abhishek Royal

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Introduction: Tuberculosis is a global public health emergency, but it is particularly acute in India, which has the world's highest tuberculosis burden. Due to overpopulation, lack of sanitation, malnutrition, low living standards, and poor socioeconomic status, among other factors, it is India's most common infectious disease. The long period of treatment is one of the main reasons for considering it as a public health emergency. Consequently, there is an increase in patient noncompliance, which leads to treatment failure, adverse treatment outcomes, and deaths. This could lead to the growth of anti-TB drug resistance. According to the WHO, approximately 558 thousand new cases of Multi-Drug Resistance Tuberculosis were diagnosed worldwide, with 8.5 percent developed Extensively Drug Resistance Tuberculosis. Methodology: This study is a program-based cross-sectional descriptive survey of adult tuberculosis patients enrolled in the Delhi-based Revised National Tuberculosis Program. The study setting was 27 NTEP districts of Delhi. (N=65,893) and Sample size- was 200; the sampling method which is used in the study was the systemic random sampling method. Results: Most of the demographic factors (age, gender, residence, and family type) were not significantly associated with adherence; marital status was found statistically significant with the treatment compliance. Hesitation while telling people about the disease and motivation to strictly follow drug schedule by healthcare workers were other factors where a significant association with drug adherence was observed. The study findings also suggest that provision of food, minimal financial and other moral support from family, counseling, discussion and politeness by healthcare providers might also facilitate adherence. Discussion and Conclusions: For TB treatment, adherence, age, sex, socioeconomic status, types of accommodations, malnutrition, and personal hygiene should all be considered; similar results were observed in previous studies. In the care of TB patients, DOTS services, health workers, and family support play a significant role. According to the country's National Strategic Plan, the Indian government has set a goal of eliminating tuberculosis by 2025 and patients' compliance with TB care and treatment adherence is very crucial to achieve this aim. A cohort study will be able to give a better understanding of factors associated with adherence since this study may have missed some defaulters who were absconding and could not be reached. Important Terms: RNTCP, NTEP, DOTS, DS-TB, DR-TB, RR-TB, MDR-TB, XDR-TB, Treatment failure, Treatment relapse, Treatment adherence.

Keywords: treatment adherence, treatment relapse, treatment failure, drug resistance tuberculosis

Procedia PDF Downloads 200

Authors: Ju-Chun Chien

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Rapid aging and depopulation could lead to serious problems, including workforce shortages and health expenditure costs. The current and predicted future LTC workforce shortages could be a real threat to Taiwan’s society. By means of comparison of data from 144 nursing aide trainees and 727 general public, the main purpose of the present study was to determine whether there were any notable differences between the two groups toward engaging in LTC services. Moreover, this study focused on recognizing the attributes of the general public who had the willingness to take LTC jobs but continue to ride the fence. A self-developed questionnaire was designed based on Ajzen’s Theory of Planned Behavior model. After conducting exploratory factor analysis (EFA) and reliability analysis, the questionnaire was a reliable and valid instrument for both nursing aide trainees and the general public. The main results were as follows: Firstly, nearly 70% of nursing aide trainees showed interest in LTC jobs. Most of them were middle-aged female (M = 46.85, SD = 9.31), had a high school diploma or lower, had unrelated work experience in healthcare, and were mostly unemployed. The most common reason for attending the LTC training program was to gain skills in a particular field. The second most common reason was to obtain the license. The third and fourth reasons were to be interested in caring for people and to increase income. The three major reasons that might push them to leave LTC jobs were physical exhaustion, payment is bad, and being looked down on. Secondly, the variables that best-predicted nursing aide trainees’ intention to engage in LTC services were having personal willingness, perceived behavior control, with high school diploma or lower, and supported from family and friends. Finally, only 11.80% of the general public reported having interest in LTC jobs (the disapproval rating was 50% for the general public). In comparison to nursing aide trainees who showed interest in LTC settings, 64.8% of the new workforce for LTC among the general public was male and had an associate degree, 54.8% had relevant healthcare experience, 67.1% was currently employed, and they were younger (M = 32.19, SD = 13.19) and unmarried (66.3%). Furthermore, the most commonly reason for the new workforce to engage in LTC jobs were to gain skills in a particular field. The second priority was to be interested in caring for people. The third and fourth most reasons were to give back to society and to increase income, respectively. The top five most commonly reasons for the new workforce to quitting LTC jobs were listed as follows: physical exhaustion, being looked down on, excessive working hours, payment is bad, and excessive job stress.

Keywords: long-term care services, nursing aide trainees, Taiwanese people, theory of planned behavior

Procedia PDF Downloads 157

Authors: Penina Orenstein

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In today’s world, particularly with COVID-19 a constant worldwide threat, organizations need greater visibility over their supply chains more than ever before, in order to find areas for improvement and greater efficiency, reduce the chances of disruption and stay competitive. The concept of supply chain mapping is one where every process and route is mapped in detail between each vendor and supplier. The simplest method of mapping involves sourcing publicly available data including news and financial information concerning relationships between suppliers. An additional layer of information would be disclosed by large, direct suppliers about their production and logistics sites. While this method has the advantage of not requiring any input from suppliers, it also doesn’t allow for much transparency beyond the first supplier tier and may generate irrelevant data—noise—that must be filtered out to find the actionable data. The primary goal of this research is to build data maps of supply chains by focusing on a layered approach. Using these maps, the secondary goal is to address the question as to whether the supply chain is re-engineered to make improvements, for example, to lower the carbon footprint. Using a drill-down approach, the end result is a comprehensive map detailing the linkages between tier-one, tier-two, and tier-three suppliers super-imposed on a geographical map. The driving force behind this idea is to be able to trace individual parts to the exact site where they’re manufactured. In this way, companies can ensure sustainability practices from the production of raw materials through the finished goods. The approach allows companies to identify and anticipate vulnerabilities in their supply chain. It unlocks predictive analytics capabilities and enables them to act proactively. The research is particularly compelling because it unites network science theory with empirical data and presents the results in a visual, intuitive manner.

Keywords: data mining, supply chain, empirical research, data mapping

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Authors: Temesgen Geremew Tefery

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Nanomaterials, due to their unique properties, have revolutionized the field of biosensing. Their functionalization, or modification with specific molecules, is crucial for enhancing their biocompatibility, selectivity, and sensitivity. This review explores recent advancements in nanomaterial functionalization for biosensing applications. We discuss various strategies, including covalent and non-covalent modifications, and their impact on biosensor performance. The use of biomolecules like antibodies, enzymes, and nucleic acids for targeted detection is highlighted. Furthermore, the integration of nanomaterials with different sensing modalities, such as electrochemical, optical, and mechanical, is examined. The future outlook for nanomaterial-based biosensing is promising, with potential applications in healthcare, environmental monitoring, and food safety. However, challenges related to biocompatibility, scalability, and cost-effectiveness need to be addressed. Continued research and development in this area will likely lead to even more sophisticated and versatile biosensing technologies.

Keywords: biosensing, nanomaterials, biotechnology, nanotechnology

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Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: A. A. AlRasheed, A. Atkins, R. Campion

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This paper focuses on using knowledge management and visualisation concepts to improve the patients and hospitals employee’s workflow. Hospitals workflow is a complex and complicated process and poor patient flow can put both patients and a hospital’s reputation at risk, and can threaten the facility’s financial sustainability. Healthcare leaders are under increased pressure to reduce costs while maintaining or increasing patient care standards. In this paper, a framework is proposed to help improving patient experience, staff satisfaction, and operational efficiency across hospitals by using knowledge management based visualisation concepts. This framework is using real-time visibility to track and monitor location and status of patients, staff, rooms, and medical equipment.

Keywords: knowledge management, improvements, visualisation, workflow

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Authors: Jo Parsons, Cath Grimley, Debra Bick, Sarah Hillman, Louise Clarke, Helen Atherton

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The problem: Vaccinations are routinely offered to pregnant women in the UK for influenza (flu), pertussis (whooping cough), and COVID-19, yet the uptake of these vaccinations in pregnancy remains low. Pregnant women are at increased risk of hospitalisation, morbidity, and mortality from these preventable illnesses, which can also expose their unborn babies to an increased risk of serious complications, including in utero death. This research aims to explore how pregnant women feel about vaccinations offered during pregnancy (flu, whooping cough, and COVID-19), particularly following the COVID-19 pandemic. It also aims to examine factors influencing women’s decisions about vaccinations during pregnancy and how they feel about their health and vulnerabilities to illness arising from the COVID-19 pandemic. The approach: This is a qualitative study involving semi-structured interviews with pregnant women and midwives in the UK. Interviews with pregnant women explored their views since the COVID-19 pandemic about vaccinations offered during pregnancy and whether the pandemic has influenced perceptions of vulnerability to illness in pregnant women. Interviews with midwives explored vaccination discussions they routinely have with pregnant women and identified some of the barriers to vaccination that pregnant women discuss with them. Pregnant women were recruited via participating hospitals and community groups. Midwives were recruited via participating hospitals and midwife-specific social media groups. All interviews were conducted remotely (using telephone or Microsoft Teams) and analysed using thematic analysis. Findings: 43 pregnant women and 16 midwives were recruited and interviewed. The findings presented will focus on data from pregnant women. Pregnant women reported a wide range of views and vaccination behaviour, and identified several factors influencing their decision whether to accept vaccinations or not. These included internal factors (comprised of beliefs about susceptibility to illness, perceptions of immunity, fear, and feelings of responsibility), other influences (including visibility of illness and external influences such as healthcare professional recommendations), vaccination-related factors (comprised of beliefs about effectiveness and safety of vaccinations, availability and accessibility of vaccinations and preferences for alternative forms of protection to vaccination) and COVID-19 specific factors (including COVID-19 vaccinations and COVID-19 specific influences). Implications: Findings identified some of the factors that affect pregnant women’s decisions when deciding to have a vaccination or not and how these decisions have been influenced by COVID-19. Findings highlight areas where healthcare professional advice needs to focus, such as the provision of information about the increased vulnerability to illnesses during pregnancy and consideration of opportunistic vaccination at hospital appointments to maximise uptake of vaccinations during pregnancy. Findings of this study will inform the development of an intervention to increase vaccination uptake amongst pregnant women.

Keywords: vaccination, pregnancy, qualitative, interviews, COVID-19

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Authors: Kelsi Hagerty, Ami Rosen, Aaliyah Heyward, Nadia Ali, Emily Brown, Erin Demo, Yue Guan, Modele Ogunniyi, Brianna McDaniels, Alanna Morris, Kunal Bhatt

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Hereditary transthyretin amyloidosis (hATTR) is a progressive, multi-systemic, and life-threatening disease caused by a disruption in the TTR protein that delivers thyroxine and retinol to the liver. This disruption causes the protein to misfold into amyloid fibrils, leading to the accumulation of the amyloid fibrils in the heart, nerves, and GI tract. Over 130 variants in the TTR gene are known to cause hATTR. The Val122Ile variant is the most common in the United States and is seen almost exclusively in people of African descent. TTR variants are inherited in an autosomal dominant fashion and have incomplete penetrance and variable expressivity. Individuals with hATTR may exhibit symptoms from as early as 30 years to as late as 80 years of age. hATTR is characterized by a wide range of clinical symptoms such as cardiomyopathy, neuropathy, carpal tunnel syndrome, and GI complications. Without treatment, hATTR leads to progressive disease and can ultimately lead to heart failure. hATTR disproportionately affects individuals of African descent; the estimated prevalence of hATTR among Black individuals in the US is 3.4%. Unfortunately, hATTR is often underdiagnosed and misdiagnosed because many symptoms of the disease overlap with other cardiac conditions. Due to the progressive nature of the disease, multi-systemic manifestations that can lead to a shortened lifespan, and the availability of free genetic testing and promising FDA-approved therapies that enhance treatability, early identification of individuals with a pathogenic hATTR variant is important, as this can significantly impact medical management for patients and their relatives. Furthermore, recent literature suggests that TTR genetic testing should be performed in all patients with suspicion of TTR-related cardiomyopathy, regardless of age, and that follow-up with genetic counseling services is recommended. Relatives of patients with hATTR benefit from genetic testing because testing can identify carriers early and allow relatives to receive regular screening and management. Despite the striking prevalence of hATTR among Black individuals, hATTR remains underdiagnosed in this patient population, and germline genetic testing for hATTR in Black individuals seems to be underrepresented, though the reasons for this have not yet been brought to light. Historically, Black patients experience a number of barriers to seeking healthcare that has been hypothesized to perpetuate the underdiagnosis of hATTR, such as lack of access and mistrust of healthcare professionals. Prior research has described a myriad of factors that shape an individual’s decision about whether to pursue presymptomatic genetic testing for a familial pathogenic variant, such as family closeness and communication, family dynamics, and a desire to inform other family members about potential health risks. This study explores these factors through 10 in-depth interviews with patients with hATTR about what factors may be contributing to the underdiagnosis of hATTR in the Black population. Participants were selected from the Emory University Amyloidosis clinic based on having a molecular diagnosis of hATTR. Interviews were recorded and transcribed verbatim, then coded using MAXQDA software. Thematic analysis was completed to draw commonalities between participants. Upon preliminary analysis, several themes have emerged. Barriers identified include i) Misdiagnosis and a prolonged diagnostic odyssey, ii) Family communication and dynamics surrounding health issues, iii) Perceptions of healthcare and one’s own health risks, and iv) The need for more intimate provider-patient relationships and communication. Overall, this study gleaned valuable insight from members of the Black community about possible factors contributing to the underdiagnosis of hATTR, as well as potential solutions to go about resolving this issue.

Keywords: cardiac amyloidosis, heart failure, TTR, genetic testing

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Authors: L. Donelle, S. Regan, R. Booth, M. Kerr, J. McMurray, D. Fitzsimmons

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Palliative home health care provision within the Canadian context is challenged by: (i) a shortage of registered nurses (RN) and RNs with palliative care expertise, (ii) an aging population, (iii) reliance on unpaid family caregivers to sustain home care services with limited support to conduct this ‘care work’, (iv) a model of healthcare that assumes client self-care, and (v) competing economic priorities. In response, an interprofessional team of service provider organizations, a software/technology provider, and health care providers developed and implemented a technology-enabled model of home care, the eShift model of palliative home care (eShift). The eShift model combines communication and documentation technology with non-traditional utilization of health human resources to meet patient needs for palliative care in the home. The purpose of this study was to investigate the structure, processes, and outcomes of the eShift model of care. Methodology: Guided by Donebedian’s evaluation framework for health care, this qualitative-descriptive study investigated the structure, processes, and outcomes care of the eShift model of palliative home care. Interviews and focus groups were conducted with health care providers (n= 45), decision-makers (n=13), technology providers (n=3) and family care givers (n=8). Interviews were recorded, transcribed, and a deductive analysis of transcripts was conducted. Study Findings (1) Structure: The eShift model consists of a remotely-situated RN using technology to direct care provision virtually to patients in their home. The remote RN is connected virtually to a health technician (an unregulated care provider) in the patient’s home using real-time communication. The health technician uses a smartphone modified with the eShift application and communicates with the RN who uses a computer with the eShift application/dashboard. Documentation and communication about patient observations and care activities occur in the eShift portal. The RN is typically accountable for four to six health technicians and patients over an 8-hour shift. The technology provider was identified as an important member of the healthcare team. Other members of the team include family members, care coordinators, nurse practitioners, physicians, and allied health. (2) Processes: Conventionally, patient needs are the focus of care; however within eShift, the patient and the family caregiver were the focus of care. Enhanced medication administration was seen as one of the most important processes, and family caregivers reported high satisfaction with the care provided. There was perceived enhanced teamwork among health care providers. (3) Outcomes: Patients were able to die at home. The eShift model enabled consistency and continuity of care, and effective management of patient symptoms and caregiver respite. Conclusion: More than a technology solution, the eShift model of care was viewed as transforming home care practice and an innovative way to resolve the shortage of palliative care nurses within home care.

Keywords: palliative home care, health information technology, patient-centred care, interprofessional health care team

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Authors: C. Brierley, H. El-Farahaty, A. Farhan

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The Leeds Parallel Corpus of Arabic-English Constitutions is a parallel corpus for the Arabic legal domain. Analysis of legal language via Corpus Linguistics techniques is an important development. In legal proceedings, a corpus-based approach to disambiguating meaning is set to replace the dictionary as an interpretative tool, and legal scholarship in the States is now attuned to the potential for Text Analytics over vast quantities of text-based legal material, following the business and medical industries. This trend is reflected in Europe: the interdisciplinary research group in Computer Assisted Legal Linguistics mines big data collections of legal and non-legal texts to analyse: legal interpretations; legal discourse; the comprehensibility of legal texts; conflict resolution; and linguistic human rights. This paper focuses on ‘dignity’ as an important aspect of the overarching concept of human rights in current constitutions across the Arab world. We have compiled a parallel, Arabic-English raw text corpus (169,861 Arabic words and 205,893 English words) from reputable websites such as the World Intellectual Property Organisation and CONSTITUTE, and uploaded and queried our corpus in Sketch Engine. Our most challenging task was sentence-level alignment of Arabic-English data. This entailed manual intervention to ensure correspondence on a one-to-many basis since Arabic sentences differ from English in length and punctuation. We have searched for morphological variants of ‘dignity’ (رامة ك, karāma) in the Arabic data and inspected their English translation equivalents. The term occurs most frequently in the Sudanese constitution (10 instances), and not at all in the constitution of Palestine. Its most frequent collocate, determined via the logDice statistic in Sketch Engine, is ‘human’ as in ‘human dignity’.

Keywords: Arabic constitution, corpus-based legal linguistics, human rights, parallel Arabic-English legal corpora

Procedia PDF Downloads 183

Authors: Nabiha Bouafia, Asma Ben Cheikh, Asma Ammar, Olfa Ezzi, Mohamed Mahjoub, Khaoula Meddeb, Imed Chouchene, Hamadi Boussarsar, Mansour Njah

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Background: Hospital acquired infections (HAI) cause significant morbidity, mortality, length of stay and hospital costs, especially in the intensive care unit (ICU), because of the debilitated immune systems of their patients and exposure to invasive devices. The aims of this study were to determine the rate and the risk factors of HAI in an ICU of a university hospital in Tunisia. Materials/Methods: A prospective study was conducted in the 8-bed adult medical ICU of a University Hospital (Sousse Tunisia) during 14 months from September 15th, 2015 to November 15th, 2016. Patients admitted for more than 48h were included. Their surveillance was stopped after the discharge from ICU or death. HAIs were defined according to standard Centers for Disease Control and Prevention criteria. Risk factors were analyzed by conditional stepwise logistic regression. The p-value of < 0.05 was considered significant. Results: During the study, 192 patients had admitted for more than 48 hours. Their mean age was 59.3± 18.20 years and 57.1% were male. Acute respiratory failure was the main reason of admission (72%). The mean SAPS II score calculated at admission was 32.5 ± 14 (range: 6 - 78). The exposure to the mechanical ventilation (MV) and the central venous catheter were observed in 169 (88 %) and 144 (75 %) patients, respectively. Seventy-three patients (38.02%) developed 94 HAIs. The incidence density of HAIs was 41.53 per 1000 patient day. Mortality rate in patients with HAIs was 65.8 %( n= 48). Regarding the type of infection, Ventilator Associated Pneumoniae (VAP) and central venous catheter Associated Infections (CVC AI) were the most frequent with Incidence density: 14.88/1000 days of MV for VAP and 20.02/1000 CVC days for CVC AI. There were 5 Peripheral Venous Catheter Associated Infections, 2 urinary tract infections, and 21 other HAIs. Gram-negative bacteria were the most common germs identified in HAIs: Multidrug resistant Acinetobacter Baumanii (45%) and Klebsiella pneumoniae (10.96%) were the most frequently isolated. Univariate analysis showed that transfer from another hospital department (p= 0.001), intubation (p < 10-4), tracheostomy (p < 10-4), age (p=0.028), grade of acute respiratory failure (p=0.01), duration of sedation (p < 10-4), number of CVC (p < 10-4), length of mechanical ventilation (p < 10-4) and length of stay (p < 10-4), were associated to high risk of HAIS in ICU. Multivariate analysis reveals that independent risk factors for HAIs are: transfer from another hospital department: OR=13.44, IC 95% [3.9, 44.2], p < 10-4, duration of sedation: OR= 1.18, IC 95% [1.049, 1.325], p=0.006, high number of CVC: OR=2.78, IC 95% [1.73, 4.487], p < 10-4, and length of stay in ICU: OR= 1.14, IC 95% [1.066,1.22], p < 10-4. Conclusion: Prevention of nosocomial infections in ICUs is a priority of health care systems all around the world. Yet, their control requires an understanding of epidemiological data collected in these units.

Keywords: healthcare associated infections, incidence, intensive care unit, risk factors

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Authors: Abdul Basit Kiani

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The software for the digital library system is a cutting-edge solution designed to revolutionize the way libraries manage and provide access to their vast collections of digital content. This advanced software leverages the power of technology to offer a seamless and user-friendly experience for both library staff and patrons. By implementing this software, libraries can efficiently organize, store, and retrieve digital resources, including e-books, audiobooks, journals, articles, and multimedia content. Its intuitive interface allows library staff to effortlessly manage cataloging, metadata extraction, and content enrichment, ensuring accurate and comprehensive access to digital materials. For patrons, the software offers a personalized and immersive digital library experience. They can easily browse the digital catalog, search for specific items, and explore related content through intelligent recommendation algorithms. The software also facilitates seamless borrowing, lending, and preservation of digital items, enabling users to access their favorite resources anytime, anywhere, on multiple devices. With robust security features, the software ensures the protection of intellectual property rights and enforces access controls to safeguard sensitive content. Integration with external authentication systems and user management tools streamlines the library's administration processes, while advanced analytics provide valuable insights into patron behavior and content usage. Overall, this software for the digital library system empowers libraries to embrace the digital era, offering enhanced access, convenience, and discoverability of their vast collections. It paves the way for a more inclusive and engaging library experience, catering to the evolving needs of tech-savvy patrons.

Keywords: software development, empowering digital libraries, digital cataloging and access, management system

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Dessy Arumsari, Ais Assana Athqiya, Mulyaminingrum

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Healthcare in remote areas is one of the major concerns in Indonesia. Building hospitals in a nation of 18.000 islands with a larger-than-life bureaucracy and problems with corruption, a critical shortage of qualified medical professionals and well-heeled patients resigned to traveling abroad for health care is a hard feat to accomplish. To assuring that all populations have access to appropriate and cost-effective care, a new solution to tackle this problem is with the presence of RV Car Clinic. This car has a concept such as a walking hospital that provides health facilities inside it. All of the health professionals who work in RV Car Clinic will do the rotation for a year in order to the equitable distribution of health workers. We need to advocate the policy makers to help realize RV Car Clinic in remote areas. Health services can be disseminated by the present of RV Car Clinic. Summarily, the local communities can get cost effectively because RV Car Clinic will come to their place and serve the health services.

Keywords: health policy, health professional, remote areas, RV Car Clinic

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Authors: Naseem M. Twaissi

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Medical professionals play an important role in society, and in general, they care more about their patients than about their personal well-being. They need to take a professional approach to maintain a work-life balance. Through a collection of primary data from 1020 medical professionals and the application of relevant statistical tools, this paper explores the pressures on medical professionals with reference to their work-life balance. This study highlights how hospital management, in addition to economic reasons, needs to identify variables to enhance the work-life balance of medical professionals so that quality healthcare facilities may be provided to the citizens of Jordan. Results indicate that formulation and implementation of policies for enhancing work-life balance together with career and retention plans for medical professionals would enhance the performance of hospitals and the quality of health care in Jordan, leading to greater societal well-being.

Keywords: work life balance, job environment, job satisfaction, employee well-being, stress, hospital industry

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Authors: Zahra BehboodiI-Moghadam, Zohre Khalajinia, Ali Reza Nikbakht Nasrabadi, Minoo Mohraz

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The purpose of our study was to explore and describe the experiences of pregnant women with HIV in Iran. A qualitative exploratory study with conventional content analysis was used. Twelve pregnant women with HIV who referred to perinatal care at the Imam Khomeini Hospital Behavioral Diseases Consultation: Center in Tehran were recruited to participate in in-depth interviews. The average age of the participants was 32.5 years. Four main themes were extracted from the data: “fear and hope, “stigma and discrimination, “marital life stability” and “trust”. The findings reveal the pregnant women living with HIV are vulnerable and need professional support. Improving the knowledge of healthcare professionals especially midwifes on pregnancy complications for women with HIV is crucial in order to provide high-quality care to pregnant women with HIV-positive.

Keywords: HIV, pregnancy, content analysis, experiences, Iran, qualitative research

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Authors: K. Mellou, G. Anastopoulos, T. Zakinthinos, C. Botsi, A. Terzidis

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‘PHILOS – Emergency health response to refugee crisis’ is a programme of the Greek Ministry of Health, implemented by the Hellenic Center for Disease Control and Prevention (HCDCP). The programme is funded by the Asylum, Migration and Integration Fund (AMIF) of EU’s DG Migration and Home Affairs. With the EU Member States accepting, the last period, accelerating migration flows, Greece inevitably occupies a prominent position in the migratory map due to this geographical location. The main objectives of the programme are a) reinforcement of the capacity of the public health system and enhancement of the epidemiological surveillance in order to cover refugees/migrant population, b) provision of on-site primary health care and psychological support services, and c) strengthening of national health care system task-force. The basic methods for achieving the aforementioned goals are: a) implementation of syndromic surveillance system at camps and enhancement of public health response with the use of mobile medical units (Sub-action A), b) enhancement of health care services inside the camps via increasing human resources and implementing standard operating procedures (Sub-action B), and c) reinforcement of the national health care system (primary healthcare units, hospitals, and emergency care spots) of affected regions with personnel (Sub-action C). As a result, 58 health professionals were recruited under sub-action 2 and 10 mobile unit teams (one or two at each health region) were formed. The main actions taken so far by the mobile units are the evaluation, of syndromic surveillance, of living conditions at camps and medical services. Also, vaccination coverage of children population was assessed, and more than 600 catch-up vaccinations were performed by the end of June 2017. Mobile units supported transportation of refugees/migrants from camps to medical services reducing the load of the National Center for Emergency Care (more than 350 transportations performed). The total number of health professionals (MD, nurses, etc.) placed at camps was 104. Common practices were implemented in the recording and collection of psychological and medical history forms at the camps. Protocols regarding maternity care, gender based violence and handling of violent incidents were produced and distributed at personnel working at camps. Finally, 290 health care professionals were placed at primary healthcare units, public hospitals and the National Center for Emergency Care at affected regions. The program has, also, supported training activities inside the camps and resulted to better coordination of offered services on site.

Keywords: migrants, refugees, public health, syndromic surveillance, national health care system, primary care, emergency health response

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Authors: Kwaku Damoah

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This study presents a comprehensive data-driven analysis to understand the evolution of adverse events (AEs) in pharmacovigilance. Utilizing data from the FDA Adverse Event Reporting System (FAERS), we employed three analytical methods: rank-based, frequency-based, and percentage change analyses. These methods assessed temporal trends and patterns in AE reporting, focusing on various drug-active ingredients and patient demographics. Our findings reveal significant trends in AE occurrences, with both increasing and decreasing patterns from 2000 to 2023. This research highlights the importance of continuous monitoring and advanced analysis in pharmacovigilance, offering valuable insights for healthcare professionals and policymakers to enhance drug safety.

Keywords: event analysis, FDA adverse event reporting system, pharmacovigilance, temporal trend analysis

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Authors: Raja Omman Zafar, Yves Rybarczyk, Johan Borg

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This article proposes a conceptual framework for the application of digital twin technology in home care. The main goal is to bridge the gap between advanced digital twin concepts and their practical implementation in home care. This study uses a literature review and thematic analysis approach to synthesize existing knowledge and proposes a structured framework suitable for homecare applications. The proposed framework integrates key components such as IoT sensors, data-driven models, cloud computing, and user interface design, highlighting the importance of personalized and predictive homecare solutions. This framework can significantly improve the efficiency, accuracy, and reliability of homecare services. It paves the way for the implementation of digital twins in home care, promoting real-time monitoring, early intervention, and better outcomes.

Keywords: digital twin, homecare, older adults, healthcare, IoT, artificial intelligence

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Authors: Pawan Hinge, Priya Gupta

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Due to cutting edge competitions between organizations and war for talent, the workforce as an asset is gaining significance. The employees are considered as the brand ambassadors of an organization, and their interactions with the clients and customers might impact directly or indirectly on the overall value of the organization. Especially, organizations in the healthcare industry the value of an organization in the perception of their employees can be one of the revenue generating and talent retention strategy. In such context, it is essential to understand that the brand awareness among employees can effect on employer brand image and brand value since the brand ambassadors are the interface between organization and customers and clients. In this exploratory study, we have adopted both quantitative and qualitative approaches for data analysis. Our study shows existing variation among nurses working in different business units of the same organization in terms of their customer interface or interactions and brand awareness.

Keywords: brand awareness, brand image, brand value, customer interface

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Authors: Asad Abbas, Muhammad Fezan Afzal, Muhammad Latif Anjum, Muhammad Azmat

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The Internet of Things (IoT) is used to link up real objects that use the internet to interact. IoT applications allow handling and operating the equipment in accordance with environmental needs, such as transportation and healthcare. IoT devices are linked together via a number of agents that act as a middleman for communications. The operation of a heat sensor differs indoors and outside because agent applications work with environmental variables. In this article, we suggest using Software Product Line (SPL) to model IoT agents and applications' features on an XML-based basis. The contextual diversity within the same domain of application can be handled, and the reusability of features is increased by XML-based feature modelling. For the purpose of managing contextual variability, we have embraced XML for modelling IoT applications, agents, and internet-connected devices.

Keywords: IoT agents, IoT applications, software product line, feature model, XML

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Authors: Sharda Kumari, Saiman Shetty

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Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

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Authors: Aria Teimourzadeh, Marc Favier, Samaneh Kakavand

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The emergence of social networks has revolutionized the exchange of information. Every behavior on these platforms contributes to the generation of data known as social network data that are processed, stored and published by the social network service providers. Hence, it is vital to investigate the role of these platforms in user data by considering the privacy measures, especially when we observe the increased number of individuals and organizations engaging with the current virtual platforms without being aware that the data related to their positioning, connections and behavior is uncovered and used by third parties. Performing analytics on social network datasets may result in the disclosure of confidential information about the individuals or organizations which are the members of these virtual environments. Analyzing separate datasets can reveal private information about relationships, interests and more, especially when the datasets are analyzed jointly. Intentional breaches of privacy is the result of such analysis. Addressing these privacy concerns requires an understanding of the nature of data being accumulated and relevant data privacy regulations, as well as motivations for disclosure of personal information on social network platforms. Some significant points about how user's online information is controlled by the influence of social factors and to what extent the users are concerned about future use of their personal information by the organizations, are highlighted in this paper. Firstly, this research presents a short literature review about the structure of a network and concept of privacy in Online Social Networks. Secondly, the factors of user behavior related to privacy protection and self-disclosure on these virtual communities are presented. In other words, we seek to demonstrates the impact of identified variables on user information disclosure that could be taken into account to explain the privacy preservation of individuals on social networking platforms. Thirdly, a few research directions are discussed to address this topic for new researchers.

Keywords: information disclosure, privacy measures, privacy preservation, social network analysis, user experience

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Authors: Maha Atout, Pippa Hemingway, Jane Seymour

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A preliminary systematic review shows that health professionals experience a tension when communicating with the parents and family members of children with life-threatening and life-limiting conditions. On the one hand, they want to promote open and honest communication, while on the other, they are apprehensive about fostering an unrealistic sense of hope. Defining the boundaries between information that might offer reasonable hope versus that which results in false reassurance is challenging. Some healthcare providers worry that instilling a false sense of hope could motivate parents to seek continued aggressive treatment for their child, which in turn might cause the patient further unnecessary suffering. To date, there has been a lack of research in the Middle East regarding how healthcare providers do or should communicate bad news; in particular, the issue of hope in the field of paediatric palliative care has not been researched thoroughly. This study aims to explore, from the perspective of patients’ mothers, physicians, and nurses, the experience of communicating and receiving bad news in the care of children with palliative care needs. Data were collected using a collective qualitative case study approach across three paediatric units in a Jordanian hospital. Two data collection methods were employed: participant observation and semi-structured interviews. The overall number of cases was 15, with a total of 56 interviews with mothers (n=24), physicians (n=12), and nurses (n=20) completed, as well as 197 observational hours logged. The findings demonstrate that mothers wanted their doctors to provide them with hopeful information about the future progression of their child’s illness. Although some mothers asked their doctors to provide them with honest information regarding the condition of their child, they still considered a sense of hope to be essential for coping with caring for their child. According to mothers, hope was critical to treatment as it helped them to stay committed to the treatment and protected them to some extent from the extreme emotional suffering that would occur if they lost hope. The health professionals agreed with the mothers on the importance of hope, so long as it was congruent with the stage and severity of each patient’s disease. The findings of this study conclude that while parents typically insist on knowing all relevant information when their child is diagnosed with a severe illness, they considered hope to be an essential part of life, and they found it very difficult to handle suffering without any glimmer of it. This study finds that using negative terms has extremely adverse effects on the parents’ emotions. Hence, although the mothers asked the doctors to be as honest as they could, they still wanted the physicians to provide them with a positive message by communicating this information in a sensitive manner including hope.

Keywords: health professionals, children, communication, hope, information, mothers, palliative care

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Authors: Hoyeon Park, Kyoung-jae Kim

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The product recommendation is a field of research that has received much attention in the recent information overload phenomenon. The proliferation of the mobile environment and social media cannot help but affect the results of the recommendation depending on how the factors of the user's situation are reflected in the recommendation process. Recently, research has been spreading attention to the context-aware recommender system which is to reflect user's contextual information in the recommendation process. However, until now, most of the context-aware recommender system researches have been limited in that they reflect the passive context of users. It is expected that the user will be able to express his/her contextual information through his/her active behavior and the importance of the context-aware recommender system reflecting this information can be increased. The purpose of this study is to propose a context-aware recommender system that can reflect the user's emotional state as an active context information to recommendation process. The context-aware recommender system is a recommender system that can make more sophisticated recommendations by utilizing the user's contextual information and has an advantage that the user's emotional factor can be considered as compared with the existing recommender systems. In this study, we propose a method to infer the user's emotional state, which is one of the user's context information, by using the user's facial expression data and to reflect it on the recommendation process. This study collects the facial expression data of a user who is looking at a specific product and the user's product preference score. Then, we classify the facial expression data into several categories according to the previous research and construct a model that can predict them. Next, the predicted results are applied to existing collaborative filtering with contextual information. As a result of the study, it was shown that the recommended results of the context-aware recommender system including facial expression information show improved results in terms of recommendation performance. Based on the results of this study, it is expected that future research will be conducted on recommender system reflecting various contextual information.

Keywords: context-aware, emotional state, recommender systems, business analytics

Procedia PDF Downloads 229

Authors: Mandayachepa C. Nyando, Lauren Suchman, Innocencia Mtalimanja, Address Malata, Tamanda Jumbe, Martha Kamanga, Peter Waiswa

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Background: Subcutaneous depot medroxyprogesterone acetate (DMPA-SC) is a new innovation in contraceptive methods that allow users to inject themselves with a hormonal contraceptive in their own homes. Self-injection (SI) of DMPA-SC has the potential to improve the accessibility of family planning to women who want it and who are capable of injecting themselves. Malawi started implementing this new innovation in 2018. SI was incorporated into the DMPA-SC delivery strategy from its outset. Methodology: This study involved two districts in Malawi where DMPA-SC SI was rolled out: Mulanje and Ntchisi. We used a qualitative cross-sectional study design where 60 in-depth interviews were conducted with women of reproductive age group stratified as 15-45 age band. These included women who were SI users, non-users, and any woman who was on any contraceptive methods. The women participants were tape-recorded, and data were transcribed and then analysed using Dedoose software, where themes were categorised into mother and child themes. Results: Women perceived DMPA SC SI as uniquely private, convenient, and less painful when self-injected. In terms of privacy, women in Mulanje and Ntchisi especially appreciated that self-injecting allowed them to use covertly from partners. Some men do not allow their spouses to use modern contraceptive methods; hence women prefer to use them covertly. “… but I first reach out to men because the strongest power is answered by men (MJ015).” In addition, women reported that SI offers privacy from family/community and less contact with healthcare providers. These aspects of privacy were especially valued in areas where there is a high degree of mistrust around family planning and among those who feel judged or antagonized purchasing contraception, such as young unmarried women. Women also valued the convenience SI provided in terms of their ability to save time by injecting themselves at home rather than visiting a healthcare provider and having more reliable access to contraception, particularly in the face of stockouts. SI allows for stocking up on doses to accommodate shifting work schedules in case of future stockouts or hard times, such as the period of COVID-19, where there was a limitation in the movement of the people. Conclusion: Our findings suggest that SI may meet the needs of many women in Malawi as long as the barriers are eliminated. The barriers women mentioned include fear of self-inject and proper storage of the DMPA SC SI, and these barriers can be eliminated by proper training. The findings also set the scene for policy revision and direction at a national level and integrate the approach with national family planning strategies in Malawi. Findings provide insights that may guide future implementation strategies, strengthen non-clinic family planning access programs and stimulate continued research.

Keywords: family planning, Malawi, Sayana press, self-injection

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

Procedia PDF Downloads 129