Search results for: Pervasive Healthcare

Authors: Peng Shen Ong, Yoong Choon Chang, Chee Pun Ooi, Ettikan K. Karuppiah, Shahirina Mohd Tahir

Abstract:

Falling has been one of the major concerns and threats to the independence of the elderly in their daily lives. With the worldwide significant growth of the aging population, it is essential to have a promising solution of fall detection which is able to operate at high accuracy in real-time and supports large scale implementation using multiple cameras. Field Programmable Gate Array (FPGA) is a highly promising tool to be used as a hardware accelerator in many emerging embedded vision based system. Thus, it is the main objective of this paper to present an FPGA-based solution of visual based fall detection to meet stringent real-time requirements with high accuracy. The hardware architecture of visual based fall detection which utilizes the pixel locality to reduce memory accesses is proposed. By exploiting the parallel and pipeline architecture of FPGA, our hardware implementation of visual based fall detection using FGPA is able to achieve a performance of 60fps for a series of video analytical functions at VGA resolutions (640x480). The results of this work show that FPGA has great potentials and impacts in enabling large scale vision system in the future healthcare industry due to its flexibility and scalability.

Keywords: Fall detection, FPGA, hardware implementation.

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Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

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Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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Authors: Mohamed Elshal, Hazim El-Mounayri, Omar El-Mounayri

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Emergency department (ED) is considered as a complex system of interacting entities: patients, human resources, software and hardware systems, interfaces, and other systems. This paper represents a research for implementing a detailed Systems Engineering (SE) approach in a mid-size hospital in central Indiana. This methodology will be applied by “The Initiative for Product Lifecycle Innovation (IPLI)” institution at Indiana University to study and solve the crowding problem with the aim of increasing throughput of patients and enhance their treatment experience; therefore, the nature of crowding problem needs to be investigated with all other problems that leads to it. The presented SE methods are workflow analysis and systems modeling where SE tools such as Microsoft Visio are used to construct a group of system-level diagrams that demonstrate: patient’s workflow, documentation and communication flow, data systems, human resources workflow and requirements, leadership involved, and integration between ER different systems. Finally, the ultimate goal will be managing the process through implementation of an executable model using commercialized software tools, which will identify bottlenecks, improve documentation flow, and help make the process faster.

Keywords: Systems modeling, ED operation, workflow modeling, systems analysis.

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Authors: Sotirios Raptis

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Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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Authors: Saleh Alumaran, Giampaolo Bella, Feng Chen

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The study of organisations’ information security cultures has attracted scholars as well as healthcare services industry to research the topic and find appropriate tools and approaches to develop a positive culture. The vast majority of studies in Saudi national health services are on the use of technology to protect and secure health services information. On the other hand, there is a lack of research on the role and impact of an organisation’s cultural dimensions on information security. This research investigated and analysed the role and impact of cultural dimensions on information security in Saudi Arabia health service. Hypotheses were tested and two surveys were carried out in order to collect data and information from three major hospitals in Saudi Arabia (SA). The first survey identified the main cultural-dimension problems in SA health services and developed an initial information security culture framework model. The second survey evaluated and tested the developed framework model to test its usefulness, reliability and applicability. The model is based on human behaviour theory, where the individual’s attitude is the key element of the individual’s intention to behave as well as of his or her actual behaviour. The research identified a set of cultural and sub-cultural dimensions in SA health information security and services.

Keywords: Behaviour theory, Culture dimensions, Electronic health records, Information security.

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Authors: Botshelo R. Sebola

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Unintended pregnancy often results in pregnancy termination. Most countries have legalised the termination of a pregnancy and pregnant adolescents can visit designated clinics without their parents’ consent. In most African and Asian countries, certain cultural practices are performed following any form of childbirth, including abortion, and such practices are ingrained in societies. The aim of this paper was to understand how women who terminated a pregnancy during adolescence coped by embracing cultural practices. A descriptive multiple case study design was adopted for the study. In-depth, semi-structured interviews and reflective diaries were used for data collection. Participants were 13 women aged 20 to 35 years who had terminated a pregnancy in adolescence. Three women kept their soiled sanitary pads, burned them to ash and waited for the rainy season to scatter the ash in a flowing stream. This ritual was performed to appease the ancestors, ask them for forgiveness and as a send-off for the aborted foetus. Five women secretly consulted Sangoma (traditional healers) to perform certain rituals. Three women isolated themselves to perform herbal cleansings, and the last two chose not to engage in any sexual activity for one year, which led to the loss of their partners. This study offers a unique contribution to understanding the solitary journey of women who terminate a pregnancy. The study challenges healthcare professionals who work in clinics that offer pregnancy termination services to look beyond releasing the foetus to advocating and providing women with the necessary care and support in performing cultural practices.

Keywords: Adolescence, case study, cultural rituals, pregnancy.

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Authors: June Tay, Ivy Chia

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There are numerous changes, both mental and physical, taking place when people age. We need to understand the different aspects required for healthy living, including meeting nutritional needs, regular physical activities to keep agility, sufficient rest and sleep to have physical and mental well-being, social engagement to avoid the risk of social isolation and depression, and access to healthcare to detect and manage chronic conditions. Promoting physical activities for an ageing population is necessary as many may have enjoyed sedentary lifestyles for some time. In our study, we evaluate the considerations when designing a computer vision video game for the elderly. We need to design some low-impact activities, such as stretching and gentle movements, because some elderly individuals may have joint pains or mobility issues. The exercise game should consist of simple movements that are easy to follow and remember. It should be fun and enjoyable so that they can be motivated to do some exercise. Social engagement can keep the elderly motivated and competitive, and they are more willing to engage in game exercises. Elderly citizens can compare their game scores and try to improve them. We propose a computer vision-based video game for the elderly that will capture and track the movement of the elderly hand pushing a ball on the screen into a circle. It can be easily set up using a PC laptop with a webcam. Our video game adhered to the design framework we employed, and it encompassed ease of use, a simple graphical interface, easy-to-play game exercise, and fun gameplay.

Keywords: Computer vision, video games, gerontology technology, caregiving.

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Authors: A. A. Alshabanat, R. B. Albacker, A. A. Basalama, A. A. Bin Salamah, A. S. Alfrayh

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The study was conducted to investigate the profile of hepatitis in Kingdom of Saudi Arabia, and to determine which age group hepatitis viruses most commonly infect. The epidemiology of viral hepatitis in Saudi Arabia has undergone major changes, concurrent with major socioeconomic developments over the last two to three decades. This disease represents a major public health problem in Saudi Arabia resulting in the need for considerable healthcare resources. A retrospective cross sectional analysis of the reported cases of viral hepatitis was conducted based on the reports of The Ministry of Health in Saudi Arabia about Hepatitis A, B and C infections in all regions from the period of January 2006 to December 2010. The study demonstrated that incidence of viral Hepatitis is decreasing, except for Hepatitis B that showed minimal increase. Of hepatitis A, B, and C, Hepatitis B virus (HBV) was the most predominant type, accounting for (53%) of the cases, followed by Hepatitis C virus (HCV) (30%) and HAV (17%). HAV infection predominates in children (5–14 years) with 60% of viral hepatitis cases, HBV in young adults (15–44 years) with 69% of viral hepatitis cases, and HCV in older adults (>45 years) with 59% of viral hepatitis cases. Despite significant changes in the prevalence of viral hepatitis A, B and C, it remains a major public health problem in Saudi Arabia; however, it showed a significant decline in the last two decades that could be attributed to the vaccination programs and the improved health facilities. Further researches are needed to identify the risk factors making a specific age group or a specific region in Saudi Arabia targeted for a specific type of hepatitis viruses.

Keywords: Epidemiology, Hepatitis, Saudi Arabia.

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Authors: Temitope O. Tokosi

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Healthcare is a human right. The sensitivity of health issues has necessitated the introduction of Enterprise Content Management (ECM) at district hospitals in the Western Cape Province of South Africa. The objective is understanding clinicians’ perception of ECM at their workplace. It is a descriptive case study design of constructivist paradigm. It employed a phenomenological data analysis method using a pattern matching deductive based analytical procedure. Purposive and s4nowball sampling techniques were applied in selecting participants. Clinicians expressed concerns and frustrations using ECM such as, non-integration with other hospital systems. Inadequate access points to ECM. Incorrect labelling of notes and bar-coding causes more time wasted in finding information. System features and/or functions (such as search and edit) are not possible. Hospital management and clinicians are not constantly interacting and discussing. Information turnaround time is unacceptably lengthy. Resolving these problems would involve a positive working relationship between hospital management and clinicians. In addition, prioritising the problems faced by clinicians in relation to relevance can ensure problem-solving in order to meet clinicians’ expectations and hospitals’ objective. Clinicians’ perception should invoke attention from hospital management with regards technology use. The study’s results can be generalised across clinician groupings exposed to ECM at various district hospitals because of professional and hospital homogeneity.

Keywords: Clinician, electronic content management, hospital, perception, technology.

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Authors: Adekunle O. Afolabi, Pekka Toivanen

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The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.

Keywords: Recommendation systems, healthcare, internet of things, real-time, homecare.

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Authors: Aya Salama

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Digital Twin has emerged as a compelling research area, capturing the attention of scholars over the past decade. It finds applications across diverse fields, including smart manufacturing and healthcare, offering significant time and cost savings. Notably, it often intersects with other cutting-edge technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, the concept of a Human Digital Twin (HDT) is still in its infancy and requires further demonstration of its practicality. HDT takes the notion of Digital Twin a step further by extending it to living entities, notably humans, who are vastly different from inanimate physical objects. The primary objective of this research was to create an HDT capable of automating real-time human responses by simulating human behavior. To achieve this, the study delved into various areas, including clustering, supervised classification, topic extraction, and sentiment analysis. The paper successfully demonstrated the feasibility of HDT for generating personalized responses in social messaging applications. Notably, the proposed approach achieved an overall accuracy of 63%, a highly promising result that could pave the way for further exploration of the HDT concept. The methodology employed Random Forest for clustering the question database and matching new questions, while K-nearest neighbor was utilized for sentiment analysis.

Keywords: Human Digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification and clustering.

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Authors: Cheryl Marie Cordeiro

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Although fisheries and aquaculture studies might seem marginal to international business (IB) studies in general, fisheries and aquaculture IB (FAIB) management is currently facing increasing pressure to meet global demand and consumption for fish in the next coming decades. In part address to this challenge, the purpose of this systematic review of literature (SLR) study is to investigate the use of the term ‘market access’ in its context of use in the generic literature and business sector discourse, in comparison to the more specific literature and discourse in fisheries, aquaculture and seafood. This SLR aims to uncover the knowledge/interest gaps between the academic subject discourses and business sector practices. Corpus driven in methodology and using a triangulation method of three different text analysis software including AntConc, VOSviewer and Web of Science (WoS) analytics, the SLR results indicate a gap in conceptual knowledge and business practices in how ‘market access’ is conceived and used in the context of the pharmaceutical healthcare industry and FAIB research and practice. While it is acknowledged that the product orientation of different business sectors might differ, this SLR study works with the assumption that both business sectors are global in orientation. These business sectors are complex in their operations from product to market. This SLR suggests a conceptual model in understanding the challenges, the potential barriers as well as avenues for solutions to developing market access for FAIB.

Keywords: Market access, fisheries and aquaculture, international business, systematic literature review.

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Authors: Atul Khurana, Rajul Rastogi, Hans-Joachim Gamperl

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The pharmaceutical companies are getting more inclined towards patient support programs (PSPs) which assist patients and/or healthcare professionals (HCPs) in more desirable disease management and cost-effective treatment. The utmost objective of these programs is patient care. The PSPs may include financial assistance to patients, medicine compliance programs, access to HCPs via phone or online chat centers, etc. The PSP has a crucial role in terms of customer acquisition and retention strategies. During the conduct of these programs, Marketing Authorisation Holder (MAH) may receive information related to concerned medicinal products, which is usually reported by patients or involved HCPs. This information may include suspected adverse reaction(s) during/after administration of medicinal products. Hence, the MAH should design PSP to comply with regulatory reporting requirements and avoid non-compliance during PV inspection. The emergence of wireless health devices is lowering the burden on patients to manually incorporate safety data, and building a significant option for patients to observe major swings in reference to drug safety. Therefore, to enhance the adoption of these programs, MAH not only needs to aware patients about advantages of the program, but also recognizes the importance of time of patients and commitments made in a constructive manner. It is indispensable that strengthening the public health is considered as the topmost priority in such programs, and the MAH is compliant to Pharmacovigilance (PV) requirements along with regulatory obligations.

Keywords: Drug safety, good pharmacovigilance practice, patient support program, pharmacovigilance.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: D. Bheenick, M. Young, M. Elmussareh, A. Ali

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Coronavirus disease 2019 (COVID-19) has had unprecedented effects on the healthcare system in the UK. The pandemic has impacted every service within secondary care, including urology. Our objective is to determine how COVID-19 has influenced acute urology admissions in a busy district general hospital in the UK. To conduct the study, retrospective data of patients presenting acutely to the urology department were collected between January 13 to March 22, 2020 (pre-lockdown period) and March 23 to May 31, 2020 (lockdown period). The nature of referrals, types of admission encountered, and management required in accordance with the new set of protocols established during the lockdown period were analysed and compared to the same data prior to UK lockdown. Included in the study were 1092 patients. The results show that an overall reduction of 32.5% was seen in the total number of admissions. A marked decrease was seen in non-urological pathology as compared to other categories. Urolithiasis showed the highest proportional increase. Treatment varied proportionately to the diagnosis, with conservative management accounting for the most likely treatment during lockdown. However, the proportion of patients requiring interventions during the lockdown period increased overall. No comparative differences were observed during the two periods in terms of source of referral, length of stay and patient age. The results of the study concluded that the admission rate showed a decrease, with no significant difference in the nature and timing of presentation. Our department was able to continue providing effective management to patients presenting acutely during the COVID-19 outbreak.

Keywords: COVID-19, lockdown, admissions, urology

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Authors: Dalyah Y. Al-Jamal, Maryam H. Eshtaiwi, Liyakathunisa Syed

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Connecting health services with technology has a huge demand as people health situations are becoming worse day by day. In fact, engaging new technologies such as Internet of Things (IOT) into the medical services can enhance the patient care services. Specifically, patients suffering from chronic diseases such as cardiac patients need a special care and monitoring. In reality, some efforts were previously taken to automate and improve the patient monitoring systems. However, the previous efforts have some limitations and lack the real-time feature needed for chronic kind of diseases. In this paper, an improved process model for patient monitoring system specialized for cardiac patients is presented. A survey was distributed and interviews were conducted to gather the needed requirements to improve the cardiac patient monitoring system. Business Process Model and Notation (BPMN) language was used to model the proposed process. In fact, the proposed system uses the IOT Technology to assist doctors to remotely monitor and follow-up with their heart patients in real-time. In order to validate the effectiveness of the proposed solution, simulation analysis was performed using Bizagi Modeler tool. Analysis results show performance improvements in the heart monitoring process. For the future, authors suggest enhancing the proposed system to cover all the chronic diseases.

Keywords: Business process model and notation, cardiac patient, cardiac monitoring, heart monitoring, healthcare, internet of things, remote patient monitoring system, process model, telemedicine, wearable sensors.

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Authors: Mehtap Dursun, E. Ertugrul Karsak, Melis Almula Karadayi

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The management of the health-care wastes is one of the most important problems in Istanbul, a city with more than 12 million inhabitants, as it is in most of the developing countries. Negligence in appropriate treatment and final disposal of the healthcare wastes can lead to adverse impacts to public health and to the environment. This paper employs a fuzzy multi-criteria group decision making approach, which is based on the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and technique for order preference by similarity to ideal solution (TOPSIS), to evaluate health-care waste (HCW) treatment alternatives for Istanbul. The evaluation criteria are determined employing nominal group technique (NGT), which is a method of systematically developing a consensus of group opinion. The employed method is apt to manage information assessed using multigranularity linguistic information in a decision making problem with multiple information sources. The decision making framework employs ordered weighted averaging (OWA) operator that encompasses several operators as the aggregation operator since it can implement different aggregation rules by changing the order weights. The aggregation process is based on the unification of information by means of fuzzy sets on a basic linguistic term set (BLTS). Then, the unified information is transformed into linguistic 2-tuples in a way to rectify the problem of loss information of other fuzzy linguistic approaches.

Keywords: Group decision making, health care waste management, multi-criteria decision making, OWA, TOPSIS, 2-tuple linguistic representation

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. Our work applies modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Sharifah Sumayyah Engku Alwi, Masrah Azrifah Azmi Murad

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The development of the information technology and Internet has been transforming the healthcare industry. The internet is continuously accessed to seek for health information and there are variety of sources, including search engines, health websites, and social networking sites. Providing more and better information on health may empower individuals, however, ensuring a high quality and trusted health information could pose a challenge. Moreover, there is an ever-increasing amount of information available, but they are not necessarily accurate and up to date. Thus, this paper aims to provide an insight of the models and frameworks related to online health information seeking of consumers. It begins by exploring the definition of information behavior and information seeking to provide a better understanding of the concept of information seeking. In this study, critical factors such as performance expectancy, effort expectancy, and social influence will be studied in relation to the value of seeking health information. It also aims to analyze the effect of age, gender, and health status as the moderator on the factors that influence online health information seeking, i.e. trust and information quality. A preliminary survey will be carried out among the health professionals to clarify the research problems which exist in the real world, at the same time producing a conceptual framework. A final survey will be distributed to five states of Malaysia, to solicit the feedback on the framework. Data will be analyzed using SPSS and SmartPLS 3.0 analysis tools. It is hoped that at the end of this study, a novel framework that can improve online health information seeking is developed. Finally, this paper concludes with some suggestions on the models and frameworks that could improve online health information seeking.

Keywords: Information behavior, information seeking, online health information, technology acceptance model, the theory of planned behavior, UTAUT.

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Authors: Jakob Renko, Deja Praprotnik, Kristina Martinovič, Igor Karnjuš

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Catheter-related bloodstream infections are a major burden for healthcare and patients. Although infections of this type cannot be completely avoided, they can be reduced by taking preventive measures. The aim of this study is to review and analyze the existing literature on preventive interventions to prevent central venous catheters (CVC) infections. A systematic literature review was carried out. The international databases CINAHL, Medline, PubMed, and Web of Science were searched using the search strategy: "catheter-related infections" AND "intensive care units" AND "prevention" AND "central venous catheter." Articles that met the inclusion and exclusion criteria were included in the study. The literature search flow is illustrated by the PRISMA diagram. The descriptive research method was used to analyze the data. Out of 554 search results, 22 surveys were included in the final analysis. We identified seven relevant preventive measures to prevent CVC infections: washing the whole body with chlorhexidine gluconate (CHG) solution, disinfecting the CVC entry site with CHG solution, use of CHG or silver dressings, alcohol protective caps, CVC care education, selecting appropriate catheter and multicomponent care bundles. Both single interventions and multicomponent care bundles have been shown to be currently effective measures to prevent CVC infections in adult patients in the ICU. None of the measures identified stood out in terms of their effectiveness. Prevention work to reduce CVC infections in the ICU is a complex process that requires the simultaneous consideration of several factors.

Keywords: Central venous access, critically ill patients, hospital-acquired complications, prevention.

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Authors: Susana Oguntoye, Naana Otoo-Oyortey, Joanne Hemmings, Kate Norman, Eiman Hussein

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There is inadequate information on the practice of female genital mutilation (FGM) in the UK, and there are often myths and perceptions within communities that influence the effectiveness of prevention programmes. This means it is difficult to address the trends and changes in the practice in the UK. To this end, FORWARD undertook novel and innovative research using the Participatory Ethnographic and Evaluative Research (PEER) method to explore the views of women from Eritrea, Sudan, Somalia and Ethiopia that live in London and Bristol (two UK cities). Women-s views, taken from PEER interviews, reflected reasons for continued practice of FGM: marriageability, the harnessing and control of female sexuality, and upholding traditions from their countries of origin. It was also clear that the main supporters of the practice were believed to be older women within families and communities. Women described the impact FGM was having on their lives as isolating. And although it was clearly considered a private and personal matter, they developed a real sense of connection with their peers within the research process. The women were overwhelmingly positive about combating the practice, although they believed it would probably take a while before it ends completely. They also made concrete recommendations on how to improve support services for women affected by FGM: Training for professionals (particularly in healthcare), increased engagement with, and outreach to, communities, culturally appropriate materials and information made available and accessible to communities, and more consequent implementation of legislation. Finally, the women asked for more empathy and understanding, particularly from health professionals. Rather than presenting FGM as a completely alien and inconceivable practice, it may help for those looking into these women-s lives and working with them to understand the social and economic context in which the practice takes place.

Keywords: Female Genital Mutilation, FemaleCircumcision/Cutting, Participatory Research, PEER method.

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Authors: Mannan Mridha, Mohammad S. Islam

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Innovative medical technologies offer more effective medical care, with less risk to patient and healthcare personnel. Medical technology and devices when properly used provide better data, precise monitoring and less invasive treatments and can be more targeted and often less costly. The Intensive Care Unit (ICU) equipped with patient monitoring, respiratory and cardiac support, pain management, emergency resuscitation and life support devices is particularly prone to medical errors for various reasons. Many people in the developing countries now wonder whether their visit to hospital might harm rather than help them. This is because; clinicians in the developing countries are required to maintain an increasing workload with limited resources and absence of well-functioning safety system. A team of experts from the medical, biomedical and clinical engineering in Sweden and Bangladesh have worked together to study the incidents, adverse events at the ICU in Bangladesh. The study included both public and private hospitals to provide a better understanding for physical structure, organization and practice in operating processes of care, and the occurrence of adverse outcomes the errors, risks and accidents related to medical devices at the ICU, and to develop a ICT based support system in order to reduce hazards and errors and thus improve the quality of performance, care and cost effectiveness at the ICU. Concrete recommendations and guidelines have been made for preparing appropriate ICT related tools and methods for improving the routine for use of medical devices, reporting and analyzing of the incidents at the ICU in order to reduce the number of undetected and unsolved incidents and thus improve the patient safety.

Keywords: Accidents reporting system, patient car and safety, safe medical devices.

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Authors: Ah-young Jeon, In-cheol Kim, Jae-hee Jung, Soo-young Ye, Jae-hyung Kim, Ki-gon Nam, Seoung-wan Baik, Jung-hoon Ro, Gye-rok Jeon

Abstract:

The aged are faced with increasing risk for falls. The aged have the easily fragile bones than others. When falls have occurred, it is important to detect this emergency state because such events often lead to more serious illness or even death. A implementation of PDA system, for detection of emergency situation, was developed using 3-axis accelerometer in this paper as follows. The signals were acquired from the 3-axis accelerometer, and then transmitted to the PDA through Bluetooth module. This system can classify the human activity, and also detect the emergency state like falls. When the fall occurs, the system generates the alarm on the PDA. If a subject does not respond to the alarm, the system determines whether the current situation is an emergency state or not, and then sends some information to the emergency center in the case of urgent situation. Three different studies were conducted on 12 experimental subjects, with results indicating a good accuracy. The first study was performed to detect the posture change of human daily activity. The second study was performed to detect the correct direction of fall. The third study was conducted to check the classification of the daily physical activity. Each test was lasted at least 1 min. in third study. The output of acceleration signal was compared and evaluated by changing a various posture after attaching a 3-axis accelerometer module on the chest. The newly developed system has some important features such as portability, convenience and low cost. One of the main advantages of this system is that it is available at home healthcare environment. Another important feature lies in low cost to manufacture device. The implemented system can detect the fall accurately, so will be widely used in emergency situation.

Keywords: Alarm System, Ambulatory monitoring, Emergency detection, Classification of activity, and 3-axis accelerometer.

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Authors: Giulia I. Pintea

Abstract:

The Roma people are a nomadic ethnic group native to India, and they are one of the most prevalent minorities in Europe. In the past, Roma were enslaved and they were imprisoned in concentration camps during the Holocaust; today, Roma are subject to hate crimes and are denied access to healthcare, education, and proper housing. The aim of this project is to analyze how the public perception of the Roma people may be influenced by antiziganist and pro-Roma institutions in Europe. In order to carry out this project, we used social network analysis to build two large social networks: The antiziganist network, which is composed of institutions that oppress and racialize Roma, and the pro-Roma network, which is composed of institutions that advocate for and protect Roma rights. Measures of centrality, density, and modularity were obtained to determine which of the two social networks is exerting the greatest influence on the public’s perception of Roma in European societies. Furthermore, data on hate crimes on Roma were gathered from the Organization for Security and Cooperation in Europe (OSCE). We analyzed the trends in hate crimes on Roma for several European countries for 2009-2015 in order to see whether or not there have been changes in the public’s perception of Roma, thus helping us evaluate which of the two social networks has been more influential. Overall, the results suggest that there is a greater and faster exchange of information in the pro-Roma network. However, when taking the hate crimes into account, the impact of the pro-Roma institutions is ambiguous, due to differing patterns among European countries, suggesting that the impact of the pro-Roma network is inconsistent. Despite antiziganist institutions having a slower flow of information, the hate crime patterns also suggest that the antiziganist network has a higher impact on certain countries, which may be due to institutions outside the political sphere boosting the spread of antiziganist ideas and information to the European public.

Keywords: Applied mathematics, oppression, Roma people, social network analysis.

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Authors: Haythem A. Nakkas, Philip J. Scott, Jim S. Briggs

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This paper reports a structured literature review of the application of Health Information Technology in developing countries, defined as the World Bank categories Low-income countries, Lower-middle-income, and Upper-middle-income countries. The aim was to identify and classify the various applications of health information technology to assess its current state in developing countries and explore potential areas of research. We offer specific analysis and application of HIT in Libya as one of the developing countries. A structured literature review was conducted using the following online databases: IEEE, Science Direct, PubMed, and Google Scholar. Publication dates were set for 2000-2013. For the PubMed search, publications in English, French, and Arabic were specified. Using a content analysis approach, 159 papers were analyzed and a total number of 26 factors were identified that affect the adoption of health information technology. Of the 2681 retrieved articles, 159 met the inclusion criteria which were carefully analyzed and classified. The implementation of health information technology across developing countries is varied. Whilst it was initially expected financial constraints would have severely limited health information technology implementation, some developing countries like India have nevertheless dominated the literature and taken the lead in conducting scientific research. Comparing the number of studies to the number of countries in each category, we found that Low-income countries and Lower-middle-income had more studies carried out than Upper-middle-income countries. However, whilst IT has been used in various sectors of the economy, the healthcare sector in developing countries is still failing to benefit fully from the potential advantages that IT can offer.

Keywords: Developing Countries, Developed Countries, Factors, Failure, Implementation, Libya, Success.

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Authors: Li-Ping Hsiao, Feng-Chuan Pan

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Leave of absence is important in maintaining a good status of human resource quality. Allowing the employees temporarily free from the routine assignments can vitalize the workers- morality and productivity. This is particularly critical to secure a satisfactory service quality for healthcare professionals of which were typically featured with labor intensive and complicated works to perform. As one of the veteran hospitals that were found and operated by the Veteran Department of Taiwan, the nursing staff of the case hospital was squeezed to an extreme minimum level under the pressure of a tight budgeting. Leave of absence on schedule became extremely difficult, especially for the intensive care units (ICU), in which required close monitoring over the cared patients, and that had more easily driven the ICU nurses nervous. Even worse, the deferred leaves were more than 10 days at any time in the ICU because of a fluctuating occupancy. As a result, these had brought a bad setback to this particular nursing team, and consequently defeated the job performance and service quality. To solve this problem and accordingly to strengthen their morality, a project team was organized across different departments specific for this. Sufficient information regarding jobs and positions requirements, labor resources, and actual working hours in detail were collected and analyzed in the team meetings. Several alternatives were finalized. These included job rotating, job combination, leave on impromptu and cross-departmental redeployment. Consequently, the deferred leave days sharply reduced 70% to a level of 3 or less days. This improvement had not only provided good shelter for the ICU nurses that improved their job performance and patient safety but also encouraged the nurses active participating of a project and learned the skills of solving problems with colleagues.

Keywords: Information, job rotating, human resource, intensive care unit.

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Authors: Marilena Ianculescu, Adriana Alexandru

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Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.

Keywords: Health management, Internet of Health Things, remote monitoring, senior patient.

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Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

Abstract:

Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: Avatar, dictionary, HamNoSys, hearing-impaired, Indian Sign Language, sign language.

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Authors: Viviane Nascimento, Dania Mehmod

Abstract:

Introduction: The Coronavirus (COVID-19) disease was firstly reported in Asia at the end of 2019 and became a pandemic at the beginning of 2020. It resulted in a significant impact over the global economy and the health care systems around the world. The immediate measure adopted worldwide to contain the virus was mainly the lockdown and curfews. This certainly had an important impact on expats workers due to the financial insecurity, culture barrier and distance from the family. Saudi Arabia has one of the largest flows of foreign workers in the world and expats are the majority of the workforce. The aim of this essay was assessing the psychological impact of COVID-19 in non-health care expats living in Saudi Arabia. Methods: The study was conducted in a construction company in Riyadh with non-health care employees. The cross-sectional study protocol was approved by the company's executive management. Employees who verbally agreed to participate in the study were asked to anonymously answer a questionnaire validated for behavioral research (DASS-21). In addition, a second questionnaire was created to assess feelings and emotions. Results: More than a third of participants screened positive for one or more psychological symptoms (depression, anxiety and stress) on the DASS-21 scale. Moreover, it was observed an increase on negative feelings on the additional questionnaire. Conclusion: This study reveals an increase on negative feelings and psychological symptoms among non-health care migrant workers during the COVID-19 pandemic. In light of this, it is crucial to understand the emotional effects caused by the pandemic on migrant workers in order to create supportive and informative strategies minimizing the emotional impact on this vulnerable group.

Keywords: COVID-19 pandemic, Saudi Arabia, psychological effects, migrant workers.

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