Search results for: medi-cal data

Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

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Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: Harini Aiyer, Kalyani Premkumar

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Health professionals are the key players who can help achieve the goals of population health equity. Social accountability (SA) of health professionals emphasizes their role in addressing issues of equity in the population they serve. Therefore, health professional education must focus on instilling SA in health professionals. There is limited literature offering a longitudinal perspective of how students sustain the practice of SA in later life. This project aims to identify the drivers of social accountability among physicians. This study employed an exploratory mixed methods design (QUAL-> Quant) to explore alumni perceptions and experiences. The qualitative data, collected via 20 in-depth, semi-structured interviews, provided an understanding of the perceptions of the alumni regarding the influence of their undergraduate learning environment on their SA. This was followed by a quantitative portion -a questionnaire designed from the themes identified from the qualitative data. Emerging themes from the study highlighted community-centered education and a focus on social and preventative medicine in both curricular and non-curricular facilitators of SA among physicians. Curricular components included opportunities to engage with the community, such as roadside clinics, community-orientation programs, and postings at a secondary hospital. Other facilitators that emerged were the faculty leading by example, a subsidized fee structure, and a system that prepared students for practice in rural and remote areas. The study offers a fresh perspective and dimension on how SA is addressed by medical schools. The findings may be adapted by medical schools to understand how their own SA initiatives have been sustained among physicians over the long run.

Keywords: community-based work, global health, health education, medical education, providing health in remote areas, social accountability

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Rajapaksha J. S. R. L., Rajapaksha R. G. D. T., Ranawaka A. U. R., Rangalla R. D. M. P., Ranwala R. D. E. B., Chandratilake M. N.

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Introduction: Lesbian, gay, bisexual, and transgender (LGBT) patients experience discrimination, insensitivity, and ignorance about LGBT-specific health needs among healthcare providers. Developing the correct attitudes among medical students towards LGBT may help provide them with optimal healthcare. Objectives: This study aimed at assessing the attitudes of medical students towards the LBGT community. Methodology: A cross-sectional descriptive study was among all the medical students in the Faculty of Medicine, University of Kelaniya, Sri Lanka, using a validated online questionnaire. The questionnaire focused on eight areas. The data were descriptively analyzed, and the demographic groups were compared. Results: 358 students completed the survey. The response rate was 34.26%. Their attitudes on traditional gender roles and comfortability in interacting with LGBT people were moderate, and they disagreed with negative LGBT social beliefs. They knew less about the origin of sexuality/gender of LGBT. Although they accepted LGBT as a part of diversity, they discouraged normalizing the social practices of LGBT people. Their acceptance and association of LGBT were moderately positive. A minority has encountered LGBT in close social circles, and the majority of them were batch-mates. Although males’ knowledge about the origin of LGBT was higher, they favoured traditional gender roles more. The religious groups showed no differences. The favourability of attitudes towards LGBT reflected respondents’ political ideology. Conclusion: Although medical students’ knowledge on the sexuality/gender basis of LGBT is poor, they have moderately favourable attitudes towards them. They accept LGBT as a part of social diversity but not their social practices. Poor knowledge, lack of encounters, cultural influences, and political ideology may have influenced their attitudes.

Keywords: medical students, attitude, LGBT, diversity

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Authors: Seyed Ziya Tabatabaei, Azimi Bin Hj Hamzah, Fatemeh Ebrahimi

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The increase in proportion of older people in Malaysia has led to a significant growth of health care demands. The aim of this study is to explore how perceived health care needs influence on quality of life among elderly Malay residents who reside in a Malaysian residential home. This study employed a method known as ethnographic research from May 2011 to January 2012. Four data collection strategies were selected as the main data-collecting tools including participant observation, field notes, in-depth interviews, and review of related documents. The nine knowledgeable participants for the present study were selected using the purposive sampling method. Two themes were identified: (1) Medical concerns: Feeling secure, lack of information, inadequate medical staff; and (2) Health promotion: Body condition, health education, physiotherapy and rehabilitation. These results could evoke the attention of policy-makers and care providers to better meet elderly residents’ health care needs.

Keywords: ethnographic study, health care needs, Malay elderly people, Malaysia, Quality of life, Residential home

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Authors: Winfred Okoe Addy, Jean Jacques Dominique Beraud

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Access control systems (ACs) are some of the most important components in safety areas. Inaccuracies of regulatory frameworks make personal policies and remedies more appropriate than standard models or protocols. This problem is exacerbated by the increasing complexity of software, such as integrated Big Data (BD) software for controlling large volumes of encrypted data and resources embedded in a dedicated BD production system. This paper proposes a general access control strategy system for the diffusion of Big Data domains since it is crucial to secure the data provided to data consumers (DC). We presented a general access control circulation strategy for the Big Data domain by describing the benefit of using designated access control for BD units and performance and taking into consideration the need for BD and AC system. We then presented a generic of Big Data access control system to improve the dissemination of Big Data.

Keywords: access control, security, Big Data, domain

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Authors: N. Khursheed, M. Fatima, S. Jamal, A. Raza, S. Rattani, Q. Ahsan, A. Rasheed, M. Jawed

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Introduction: Antibiotics are among the commonly prescribed medicines to treat bacterial infections. Their misuse intensifies resistance, and overuse incurs heavy losses to the healthcare system in terms of increased treatment costs and enhanced disease burden. Studies show that 40% of empirically used antibiotics are irrationally utilized. The objective of this study was to evaluate prescribing pattern of antibiotics at six public sector tertiary care hospitals across Pakistan. Methods: A multicenter cross-sectional point prevalence survey (PPS) was conducted in selected wards of six public sector tertiary care hospitals in Pakistan as part of the Clinical Engagement program by Fleming Fund Country Grant Pakistan in collaboration with Indus Hospital & Health Network (IHHN) from February to March 2021, these included Jinnah Postgraduate Medical Center and Dr. Ruth K. M. Pfau Civil Hospital from Karachi, Sheikh Zayed Hospital Lahore, Nishtar Medical University Hospital Multan, Medical Teaching Institute Hayatabad Medical Complex Peshawar, and Provincial Headquarters Hospital Gilgit. WHO PPS methodology was used for data collection (Hospital, ward, and patient level data was collected). Data was entered into the open-source Kobo Collect application and was analyzed using SPSS (version 22.0). Findings: Medical records of 837 in-patients were surveyed, of which the prevalence of antibiotics use was 78.5%. The most commonly prescribed antimicrobial was Ceftriaxone (21.7%) which is categorized in the Watch group of WHO AWaRe Classification, followed by Metronidazole (17.3%), Cefoperazone/Sulbactam (8.4%), Co-Amoxiclav (6.3%) and Piperacillin/Tazobactam (5.9%). The antibiotics were prescribed largely for surgical prophylaxis (36.7%), followed by community-acquired infections (24.7%). One antibiotic was prescribed to 46.7%, two to 39.9%, and three or more to 12.5 %. Two of six (30%) hospitals had functional drug and therapeutic committees, three (50%) had infection prevention and control committees, and one facility had an antibiotic formulary. Conclusion: Findings demonstrate high consumption of broad-spectrum antimicrobials and emphasizes the importance of expanding the antimicrobial stewardship program. Mentoring clinical teams will help to rationalize antimicrobial use.

Keywords: antimicrobial resistance, antimicrobial stewardship, point prevalence survey, antibiotics

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Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Vichayada Laohapiboolkul

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Introduction: As the legal use of cannabis is being widely accepted throughout the world, medical cannabis has been explored in order to become an alternative cure for patients. Tetrahydrocannabinol (THC) and Cannabidiol (CBD) are natural cannabinoids found in the Cannabis plant which is proved to have positive treatment for various diseases and symptoms such as chronic pain, neuropathic pain, spasticity resulting from multiple sclerosis, reduce cancer-associated pain, autism spectrum disorders (ASD), dementia, cannabis and opioid dependence, psychoses/schizophrenia, general social anxiety, posttraumatic stress disorder, anorexia nervosa, attention-deficit hyperactivity disorder, and Tourette's disorder. Regardless of all the medical benefits, THC, if not metabolized, can lead to mild up to severe adverse drug reactions (ADR). The enzyme CYP2C19 was found to be one of the metabolizers of THC. However, the suballele CYP2C19*2 manifests as a poor metabolizer which could lead to higher levels of THC than usual, possibly leading to various ADRs. Objective: The aim of this study was to investigate the distribution of CYP2C19, specifically CYP2C19*2, genes in Thai patients treated with medical cannabis along with adverse drug reactions. Materials and Methods: Clinical data and EDTA whole blood for DNA extraction and genotyping were collected from patients for this study. CYP2C19*2 (681G>A, rs4244285) genotyping was conducted using the Real-time PCR (ABI, Foster City, CA, USA). Results: There were 42 medical cannabis-induced ADRs cases and 18 medical cannabis tolerance controls who were included in this study. A total of 60 patients were observed where 38 (63.3%) patients were female and 22 (36.7%) were male, with a range of age approximately 19 - 87 years. The most apparent ADRs for medical cannabis treatment were dry mouth/dry throat (76.7%), followed by tachycardia (70%), nausea (30%) and a few arrhythmias (10%). In the total of 27 cases, we found a frequency of 18 CYP2C19*1/*1 alleles (normal metabolizers, 66.7%), 8 CYP2C19*1/*2 alleles (intermediate metabolizers, 29.6%) and 1 CYP2C19*2/*2 alleles (poor metabolizers, 3.7%). Meanwhile, 63.6% of CYP2C19*1/*1, 36.3% and 0% of CYP2C19*1/*2 and *2/*2 in the tolerance controls group, respectively. Conclusions: This is the first study to confirm the distribution of CYP2C19*2 allele and the prevalence of poor metabolizer genes in Thai patients who received medical cannabis for treatment. Thus, CYP2C19 allele might serve as a pharmacogenetics marker for screening before initiating treatment.

Keywords: medical cannabis, adverse drug reactions, CYP2C19, tetrahydrocannabinol, poor metabolizer

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Authors: Zyra Cheska Hidalgo, Joehiza Mae Renon, Kzarina Buen, Girlie Mitrado

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ABSTRACT: The global coronavirus disease (COVID-19) has dramatically impacted the lives of many, including education and our economy. Thus, it presents a massive challenge for medical education as instructors are mandated to deliver their lectures virtually to ensure the continuity of the medical education process and ensure students' safety. The purpose of this research paper is to determine the lived experiences of paramedical students who are engaged in virtual hands-on learning and to determine the different coping strategies they used to deal with virtual hands-on learning. The researchers used the survey method of descriptive research design to determine the lived experiences and coping strategies of twenty (20) paramedical students from Lorma Colleges (particularly the College of Medicine Department). The data were collected through online questionnaires, particularly with the use of google forms. This study shows technical issues, difficulty in adapting styles, distractions and time management issues, mental and physical health issues, and lack of interest and motivation are the most common problems and challenges experienced by paramedical students. On the other hand, the coping strategies used by paramedical students to deal with those challenges include time management, engagement in leisure activities, acceptance of responsibilities, studying, and adapting. With the data gathered, the researchers concluded that virtual hands-on learning effectively increases the knowledge of paramedical students. However, teaching and learning barriers must have to be considered to implement virtual hands-on learning successfully.

Keywords: virtual hands-on learning, E-learning, paramedical students, medical education

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study explored whether academic emotion, major satisfaction, and learning flow are associated with academic achievement in medical school. We know that emotion and affective factors are important factors in students' learning and performance. Emotion has taken the stage in much of contemporary educational psychology literature, no longer relegated to secondary status behind traditionally studied cognitive constructs. Medical school students (n=164) completed academic emotion, major satisfaction, and learning flow online survey. Academic performance was operationalized as students' average grade on two semester exams. For data analysis, correlation analysis, multiple regression analysis, hierarchical multiple regression analyses and ANOVA were conducted. The results largely confirmed the hypothesized relations among academic emotion, major satisfaction, learning flow and academic achievement. Positive academic emotion had a correlation with academic achievement (β=.191). Positive emotion had 8.5% explanatory power for academic achievement. Especially, sense of accomplishment had a significant impact on learning performance (β=.265). On the other hand, negative emotion, major satisfaction, and learning flow did not affect academic performance. Also, there were differences in sense of great (F=5.446, p=.001) and interest (F=2.78, p=.043) among positive emotion, boredom (F=3.55, p=.016), anger (F=4.346, p=.006), and petulance (F=3.779, p=.012) among negative emotion by grade. This study suggested that medical students' positive emotion was an important contributor to their academic achievement. At the same time, it is important to consider that some negative emotions can act to increase one’s motivation. Of particular importance is the notion that instructors can and should create learning environment that foster positive emotion for students. In doing so, instructors improve their chances of positively impacting students’ achievement emotions, as well as their subsequent motivation, learning, and performance. This result had an implication for medical educators striving to understand the personal emotional factors that influence learning and performance in medical training.

Keywords: academic achievement, learning emotion, learning flow, major satisfaction

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Authors: Adelson G. Guillarte, M. D., Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Patients with malignant middle cerebral infarction (MCA) (with massive brain swelling and herniation) were reported to have a mortality rate of 80% even with the appropriate conservative medical therapy. European Trials (DECIMAL, DESTINY I, and II, HAMLET) showed significant improvement in mortality and functional outcome with hemicraniectomy. No known published local studies in the region, thus a local study is vital. This is a single center, retrospective, descriptive, cross-sectional, chart review study which includes ≥18 year-old patients with malignant MCA infarction, who underwent hemicraniectomy, and those who were given conservative medical therapy alone, from January 2008 to December 2012 at Perpetual Succour Hospital. Excluded were patients whose charts are with insufficient data, prior MCA stroke, with concomitant intracerebral hemorrhage and with other serious medical conditions or terminal illnesses. Minimum of 32 populations were needed. Data were presented in mean, standard deviation, frequency and percentage distribution. Man n Whitney U test and Chi Square test were used. P-values lesser than 0.05 alpha were considered statistically significant. A total of 672 stroke patients were admitted. 34 patients pass the inclusion criteria. 9 underwent hemicraniectomy and 25 were treated by conservative medical therapy alone. Although not statistically significant (64% vs 33%, p=0.112) there were more patients noted improved in the conservative treatment group. Meanwhile, the Hemicraniectomy group have increased percentage of mortality (67%) (p=0.112). There was a decreasing trend in the average NIHSS score in both groups from admission to post-op 7 days (p=0.198, p=0.78). A bigger multicenter prospective study is recommended to control inherent biases and limitations of a retrospective and smaller study.

Keywords: cerebral infarct, hemicraniectomy, ischemic stroke, malignant middle cerebral artery (MCA) infarct

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Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi

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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.

Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model

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Authors: Qi En Han, Si En Wai, Eugene Quek

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As one of the two Academic Medical Centres (AMCs) in Singapore, SingHealth Duke-NUS AMC strives to improve patients’ lives through excellent clinical care, research and education. These efforts are enhanced with the establishment of Academic Clinical Programmes (ACPs). Each ACP brings together specialists in a particular discipline from different institutions to maximize the power of shared knowledge and resources. Initiated by Surgery ACP, the student research mentorship programme is a programme designed to facilitate engagement between medical students and the surgical faculty. The programme offers mentors not only the opportunity to supervise research but also to nurture future clinician scientists. In turn, medical students acquire valuable research experience which may be useful in their future careers. The programme typically lasts one year, depending on the students’ commitment. Surgery ACP matches students’ research interests with the mentor's area of expertise whenever possible. Surgery ACP organizes informal tea sessions to bring students and prospective mentors together. Once a match is made, the pair is required to submit a project proposal which includes the title, proposed start and end dates, ethical and biosafety considerations and project details. The mentees either think of their own research question with guidance from the mentors or join an existing project. The mentees may participate in data collection, data analysis, manuscript writing and conference presentation. The progress of each research project is monitored through half-yearly progress report. The mentees report problems encountered or changes made to existing proposal on top of the progress made. A total of 18 mentors were successfully paired with 36 mentees since 2013. Currently, there are 23 on-going and 13 completed projects. The mentees are encouraged to present their projects at conferences and to publish in peer-reviewed journals. Six mentees have presented their completed projects at local or international conferences and one mentee has her work published. To further support student research, Surgery ACP organized a Research Day in 2015 to recognize their research efforts and to showcase their wide-range of research. Surgery ACP recognizes that early exposure of medical students to research is important in developing them into clinician scientists. As interest in research take time to develop and are usually realized during various research attachments, it is crucial that programmes such as the student research mentorship programme exist. Surgery ACP will continue to build on this programme.

Keywords: academic clinical programme, clinician scientist, medical student, mentoring

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Authors: Mehravar Javid, Laura Reid Harris, Zahra Khodadadi, Rachel Walton

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The study aimed to explore commitment precedence through self-expansion among students at the Medical Science University of Shiraz, Iran. Method: The statistical population was comprised of students at Shiraz University of Medical Science during the academic years 2013 to 2014. Using random sampling, 133 married students (50 males and 83 females) were selected. The commitment condition of this studied group was assessed using Adam and Jones' (1999) Marital Commitment Dimensions Scale (DCI), and self-expansion was measured using Aron and Lewandowski's (2002) Self-Expansion Questionnaire. Simple regression analyses investigated commitment precedence via self-expansion. Results: The data revealed a positive correlation between total commitment (r=0.35, p < 0.01), the subscales of commitment to the spouse (r=0.43, p < 0.01), and commitment to marriage (r=0.31, p < 0.01). Regression analyses indicated that perceived self-expansion positively correlated with commitment to marital relationships in married students. The findings suggest that an increased possibility of self-expansion in a marital relationship corresponds with heightened commitment.

Keywords: commitment to marital relationship, married students, relationship dynamics, self-expansion

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Authors: Mangala. Sadasivan, Mary Hughes, Bryan Kelly

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Medical Education must focus on bridging the gap between teaching and learning when training pre-clinical year students in skills needed to keep up with medical knowledge and to meet the demands of health care in the future. The authors were interested in showing that a 3-S Model (building strength, developing stamina, and increasing speed) using a bridged curriculum design helps connect teaching and learning and improves students’ retention of basic science and clinical knowledge. The authors designed three learning modules using the 3-S Model within a systems course in a pre-clerkship medical curriculum. Each module focused on a bridge (concept map) designed by the instructor for specific content delivered to students in the course. This with-in-subjects design study included 304 registered MSU osteopathic medical students (3 campuses) ranked by quintile based on previous coursework. The instructors used the bridge to create self-directed learning exercises (building strength) to help students master basic science content. Students were video coached on how to complete assignments, and given pre-tests and post-tests designed to give them control to assess and identify gaps in learning and strengthen connections. The instructor who designed the modules also used video lectures to help students master clinical concepts and link them (building stamina) to previously learned material connected to the bridge. Boardstyle practice questions relevant to the modules were used to help students improve access (increasing speed) to stored content. Unit Examinations covering the content within modules and materials covered by other instructors teaching within the units served as outcome measures in this study. This data was then compared to each student’s performance on a final comprehensive exam and their COMLEX medical board examinations taken some time after the course. The authors used mean comparisons to evaluate students’ performances on module items (using 3-S Model) to non-module items on unit exams, final course exam and COMLEX medical board examination. The data shows that on average, students performed significantly better on module items compared to non-module items on exams 1 and 2. The module 3 exam was canceled due to a university shut down. The difference in mean scores (module verses non-module) items disappeared on the final comprehensive exam which was rescheduled once the university resumed session. Based on Quintile designation, the mean scores were higher for module items than non-module items and the difference in scores between items for Quintiles 1 and 2 were significantly better on exam 1 and the gap widened for all Quintile groups on exam 2 and disappeared in exam 3. Based on COMLEX performance, all students on average as a group, whether they Passed or Failed, performed better on Module items than non-module items in all three exams. The gap between scores of module items for students who passed COMLEX to those who failed was greater on Exam 1 (14.3) than on Exam 2 (7.5) and Exam 3 (10.2). Data shows the 3-S Model using a bridge effectively connects teaching and learning

Keywords: bridging gap, medical education, teaching and learning, model of learning

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Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

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The outbreak of the COVID-19 epidemic has caused great difficulties for South-South cooperation, but there are also opportunities. China’s health diplomacy has changed from dispatching medical teams, assisting in the construction of hospitals, and encouraging medical investment in the Africa health sector. This paper adopted a retrospective review of China’s health diplomacy in Africa from 1963 to 2020. Findings suggested that China has a preference for aiding Africa health infrastructure and sending medical teams to African countries. China’s health diplomacy in Africa is a success and has established secure diplomatic relations with African countries, thanks to the medical and health assistance to Africa over 60 years. This research contributes to the literature of health diplomacy and foreign relations and indicates that China’s health aid has fostered cooperation at the medical and diplomatic levels.

Keywords: Africa, china’s health diplomacy, COVID-19, bilateral relations

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Authors: Victor Au, Khin Maung Than, Zaw Win Aung, Linawati Jumat

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Background & Objectives: Cardiac arrests can occur anywhere or anytime, and most of the cases will be brought to the emergency department except the cases that happened in at in-patient setting. Raja IsteriPangiran Anak Saleha (RIPAS) Hospital is the only tertiary government hospital which located in Brunei Muara district and received all referral from other Brunei districts. Data of cardiac arrests in Brunei Darussalam scattered between Emergency Medical Ambulance Services (EMAS), Emergency Department (ED), general inpatient wards, and Intensive Care Unit (ICU). In this audit, we only focused on cardiac arrest cases which had happened or presented to the emergency department RIPAS Hospital. Theobjectives of this audit were to look at demographic of cardiac arrest cases and the survival to discharge rate of In-Hospital Cardiac Arrest (IHCA) and Out-Hospital Cardiac Arrest (OHCA). Methodology: This audit retrospective study was conducted on all cardiac arrest cases that underwent Cardiopulmonary Resuscitation (CPR) in ED RIPAS Hospital, Brunei Muara, in the year 2019-2020. All cardiac arrest cases that happened or were brought in to emergency department were included. All the relevant data were retrieved from ED visit registry book and electronic medical record “Bru-HIMS” with keyword diagnosis of “cardiac arrest”. Data were analyzed and tabulated using Excel software. Result: 313 cardiac arrests were recorded in the emergency department in year 2019-2020. 92% cases were categorized as OHCA, and the remaining 8% as IHCA. Majority of the cases were male with age between 50-60 years old. In OHCA subgroup, only 12.4% received bystander CPR, and 0.4% received Automatic External Defibrillator (AED) before emergency medical personnel arrived. Initial shockable rhythm in IHCA group accounted for 12% compare to 4.9% in OHCA group. Outcome of ED resuscitation, 32% of IHCA group achieved return of spontaneous circulation (ROSC) with a survival to discharge rate was 16%. For OHCA group, 12.35% achieved ROSC, but unfortunately, none of them survive till discharge. Conclusion: Standardized registry for cardiac arrest in the emergency department is required to provide valid baseline data to measure the quality and outcome of cardiac arrest. Zero survival rate for out hospital cardiac arrest is very concerning, and it might represent the significant breach in cardiac arrest chains of survival. Systematic prospective data collection is needed to identify contributing factors and to improve resuscitation outcome.

Keywords: cardiac arrest, OHCA, IHCA, resuscitation, emergency department

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Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

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Authors: H. Yousefnia, S. Zolghadri, S. Shanesazzadeh, A.Lahooti, A. R. Jalilian

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In this study, 68Ga-ECC and 67Ga-ECC were both prepared with the radiochemical purity of higher than 97% in less than 30 min. The biodistribution data for 68Ga-ECC showed the extraction of the most of the activity from the urinary tract. The absorbed dose was estimated based on biodistribution data in mice by the medical internal radiation dose (MIRD) method. Comparison between human absorbed dose estimation for these two agents indicated the values of approximately ten-fold higher after injection of 67Ga-ECC than 68Ga-ECC in the most organs. The results showed that 68Ga-ECC can be considered as a more potential agent for renal imaging compared to 67Ga-ECC.

Keywords: effective absorbed dose, ethylenecysteamine cysteine, Ga-67, Ga-68

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Authors: Abdullah Alsaeed

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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Kay-Anne Haykal, Issack Biyong

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The post-traumatic stress disorder (PTSD) rises from exposure to a traumatic event and appears by a persistent experience of this event. Several psychiatric co-morbidities are associated with PTSD and include mood disorders, anxiety disorders, and substance abuse. The main objective was to compare the criteria for PTSD according to the literature to those used to diagnose a patient in a francophone hospital and to check the correspondence of these two criteria. 700 medical charts of admitted patients on the medicine or psychiatric unit at the Montfort Hospital were identified with the following diagnoses: major depressive disorder, bipolar disorder, anxiety disorder, substance abuse, and PTSD for the period of time between April 2005 and March 2006. Multiple demographic criteria were assembled. Also, for every chart analyzed, the PTSD criteria, according to the Manual of Mental Disorders (DSM) IV were found, identified, and grouped according to pre-established codes. An analysis using the receiver operating characteristic (ROC) method was elaborated for the study of data. A sample of 57 women and 50 men was studied. Age was varying between 18 and 88 years with a median age of 48. According to the PTSD criteria in the DSM IV, 12 patients should have the diagnosis of PTSD in opposition to only two identified in the medical charts. The ROC method establishes that with the combination of data from PTSD and depression, the sensitivity varies between 0,127 and 0,282, and the specificity varies between 0,889 and 0,917. Otherwise, if we examine the PTSD data alone, the sensibility jumps to 0.50, and the specificity varies between 0,781 and 0,895. This study confirms the presence of an underdiagnosed and treated PTSD that causes severe perturbations for the affected individual.

Keywords: post-traumatic stress disorder, co-morbidities, diagnosis, mental health disorders

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

Procedia PDF Downloads 270

Authors: Zahra Asgharpour, Eric Renteria, Sebastian De Boodt

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There is a growing trend towards personalization of medical care, as evidenced by the emphasis on outcomes based medicine, the latest developments in CT and MR imaging and personalized treatment in a variety of surgical disciplines. 3D Printing has been introduced and applied in the medical field since 2000. The first applications were in the field of dental implants and custom prosthetics. According to recent publications, 3D printing in the medical field has been used in a wide range of applications which can be organized into several categories including implants, prosthetics, anatomical models and tissue bioprinting. Some of these categories are still in their infancy stage of the concept of proof while others are in application phase such as the design and manufacturing of customized implants and prosthesis. The approach of 3D printing in this category has been successfully used in the health care sector to make both standard and complex implants within a reasonable amount of time. In this study, some of the clinical applications of 3D printing in design and manufacturing of a patient-specific hip implant would be explained. In cases where patients have complex bone geometries or are undergoing a complex revision on hip replacement, the traditional surgical methods are not efficient, and hence these patients require patient-specific approaches. There are major advantages in using this new technology for medical applications, however, in order to get this technology widely accepted in medical device industry, there is a need for gaining more acceptance from the medical device regulatory offices. This is a challenge that is moving onward and will help the technology find its way at the end as an accepted manufacturing method for medical device industry in an international scale. The discussion will conclude with some examples describing the future directions of 3D Medical Printing.

Keywords: CT/MRI, image processing, 3D printing, medical devices, patient specific implants

Procedia PDF Downloads 279

Authors: K. Hardy, A. Maurushat

Abstract:

Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

Procedia PDF Downloads 349

Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

Procedia PDF Downloads 89