Displaying publications 41 - 60 of 910 in total

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  1. Yao K, Uedo N, Muto M, Ishikawa H, Cardona HJ, Filho ECC, et al.
    EBioMedicine, 2016 Jul;9:140-147.
    PMID: 27333048 DOI: 10.1016/j.ebiom.2016.05.016
    BACKGROUND: In many countries, gastric cancer is not diagnosed until an advanced stage. An Internet-based e-learning system to improve the ability of endoscopists to diagnose gastric cancer at an early stage was developed and was evaluated for its effectiveness.

    METHODS: The study was designed as a randomized controlled trial. After receiving a pre-test, participants were randomly allocated to either an e-learning or non-e-learning group. Only those in the e-learning group gained access to the e-learning system. Two months after the pre-test, both groups received a post-test. The primary endpoint was the difference between the two groups regarding the rate of improvement of their test results.

    FINDINGS: 515 endoscopists from 35 countries were assessed for eligibility, and 332 were enrolled in the study, with 166 allocated to each group. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group were included in the analysis. The mean improvement rate (standard deviation) in the e-learning and non-e-learning groups was 1·24 (0·26) and 1·00 (0·16), respectively (P<0·001).

    INTERPRETATION: This global study clearly demonstrated the efficacy of an e-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039).

    Matched MeSH terms: Learning
  2. Yang T, Xiao Y, Zhang Z, Liang Y, Li G, Zhang M, et al.
    Sci Rep, 2018 09 28;8(1):14518.
    PMID: 30266999 DOI: 10.1038/s41598-018-32757-9
    Soft robots driven by stimuli-responsive materials have their own unique advantages over traditional rigid robots such as large actuation, light weight, good flexibility and biocompatibility. However, the large actuation of soft robots inherently co-exists with difficulty in control with high precision. This article presents a soft artificial muscle driven robot mimicking cuttlefish with a fully integrated on-board system including power supply and wireless communication system. Without any motors, the movements of the cuttlefish robot are solely actuated by dielectric elastomer which exhibits muscle-like properties including large deformation and high energy density. Reinforcement learning is used to optimize the control strategy of the cuttlefish robot instead of manual adjustment. From scratch, the swimming speed of the robot is enhanced by 91% with reinforcement learning, reaching to 21 mm/s (0.38 body length per second). The design principle behind the structure and the control of the robot can be potentially useful in guiding device designs for demanding applications such as flexible devices and soft robots.
    Matched MeSH terms: Machine Learning*
  3. Yang S, Li X, Jiang Z, Xiao M
    PLoS One, 2023;18(10):e0290126.
    PMID: 37844110 DOI: 10.1371/journal.pone.0290126
    Based on the data of the Chinese A-share listed firms in China Shanghai and Shenzhen Stock Exchange from 2014 to 2021, this article explores the relationship between common institutional investors and the quality of management earnings forecasts. The study used the multiple linear regression model and empirically found that common institutional investors positively impact the precision of earnings forecasts. This article also uses graph neural networks to predict the precision of earnings forecasts. Our findings have shown that common institutional investors form external supervision over restricting management to release a wide width of earnings forecasts, which helps to improve the risk warning function of earnings forecasts and promote the sustainable development of information disclosure from management in the Chinese capital market. One of the marginal contributions of this paper is that it enriches the literature related to the economic consequences of common institutional shareholding. Then, the neural network method used to predict the quality of management forecasts enhances the research method of institutional investors and the behavior of management earnings forecasts. Thirdly, this paper calls for strengthening information sharing and circulation among institutional investors to reduce information asymmetry between investors and management.
    Matched MeSH terms: Machine Learning
  4. Yang J, Peng MY, Wong S, Chong W
    Front Psychol, 2021;12:584976.
    PMID: 33868072 DOI: 10.3389/fpsyg.2021.584976
    The COVID-19 pandemic at the beginning of 2020 has changed the conventional learning mode for most students at schools all over the world, and the e-learning at home has become a new trend. Taking Chinese college students as the research subject and drawing on the stimulus-organism-response (S-O-R) model, this paper examines the relationship between the peer referent, perceived closeness, and perceived control and the learning engagement. Using data from 377 college students who have used e-learning, this study shows that perceived closeness, perceived control, and peer referents in e-learning have a positive effect on the self-efficacy and well-being of students, thus improving students' enthusiasm for learning. Our intent is to assist researchers, instructors, designers, and others in identifying effective methods to conceptualize and measure student engagement in e-learning.
    Matched MeSH terms: Learning
  5. Yahya N, Ebert MA, Bulsara M, House MJ, Kennedy A, Joseph DJ, et al.
    Med Phys, 2016 May;43(5):2040.
    PMID: 27147316 DOI: 10.1118/1.4944738
    Given the paucity of available data concerning radiotherapy-induced urinary toxicity, it is important to ensure derivation of the most robust models with superior predictive performance. This work explores multiple statistical-learning strategies for prediction of urinary symptoms following external beam radiotherapy of the prostate.
    Matched MeSH terms: Machine Learning*
  6. Yahaya R, Zahary MN, Othman Z, Ismail R, Nik Him NAS, Abd Aziz A, et al.
    Heliyon, 2020 May;6(5):e03948.
    PMID: 32426546 DOI: 10.1016/j.heliyon.2020.e03948
    Introduction: Schizophrenia is a chronic mental illness with clusters of symptoms, including cognitive impairment. This study aimed to explore the effect of Tualang Honey (TH) on cognitive domains, especially as it pertained to the verbal memory of schizophrenia patients.

    Method: This was a cross-sectional study involved 80 individuals, diagnosed with schizophrenia. The Malay Version Auditory Verbal Learning Test (MVAVLT) was used. Data were analysed using SPSS 20.0 software. Intention to treat analysis was applied.

    Result: A comparison of the total learning score at eight weeks between the two groups based on time effect and time-treatment interaction favoured TH group.

    Conclusion: This study concludes that by supplementing schizophrenia patients with 8-week of TH did improve total learning performance across domains in the immediate memory among patients with schizophrenia.

    Matched MeSH terms: Learning; Verbal Learning
  7. Xu M, Abdullah NA, Md Sabri AQ
    Comput Biol Chem, 2024 Feb;108:107997.
    PMID: 38154318 DOI: 10.1016/j.compbiolchem.2023.107997
    This work focuses on data sampling in cancer-gene association prediction. Currently, researchers are using machine learning methods to predict genes that are more likely to produce cancer-causing mutations. To improve the performance of machine learning models, methods have been proposed, one of which is to improve the quality of the training data. Existing methods focus mainly on positive data, i.e. cancer driver genes, for screening selection. This paper proposes a low-cancer-related gene screening method based on gene network and graph theory algorithms to improve the negative samples selection. Genetic data with low cancer correlation is used as negative training samples. After experimental verification, using the negative samples screened by this method to train the cancer gene classification model can improve prediction performance. The biggest advantage of this method is that it can be easily combined with other methods that focus on enhancing the quality of positive training samples. It has been demonstrated that significant improvement is achieved by combining this method with three state-of-the-arts cancer gene prediction methods.
    Matched MeSH terms: Machine Learning
  8. Wu M, Lu Y, Yang W, Wong SY
    Front Comput Neurosci, 2020;14:564015.
    PMID: 33469423 DOI: 10.3389/fncom.2020.564015
    Cardiovascular diseases (CVDs) are the leading cause of death today. The current identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a medical monitoring technology recording cardiac activity. Unfortunately, looking for experts to analyze a large amount of ECG data consumes too many medical resources. Therefore, the method of identifying ECG characteristics based on machine learning has gradually become prevalent. However, there are some drawbacks to these typical methods, requiring manual feature recognition, complex models, and long training time. This paper proposes a robust and efficient 12-layer deep one-dimensional convolutional neural network on classifying the five micro-classes of heartbeat types in the MIT- BIH Arrhythmia database. The five types of heartbeat features are classified, and wavelet self-adaptive threshold denoising method is used in the experiments. Compared with BP neural network, random forest, and other CNN networks, the results show that the model proposed in this paper has better performance in accuracy, sensitivity, robustness, and anti-noise capability. Its accurate classification effectively saves medical resources, which has a positive effect on clinical practice.
    Matched MeSH terms: Machine Learning
  9. Woon LS, Mohd Daud TI, Tong SF
    BMC Med Educ, 2023 Nov 09;23(1):851.
    PMID: 37946151 DOI: 10.1186/s12909-023-04834-9
    BACKGROUND: At the Faculty of Medicine of the National University of Malaysia, a virtual patient software program, DxR Clinician, was utilised for the teaching of neurocognitive disorder topics during the psychiatry posting of undergraduate medical students in a modified team-based learning (TBL) module. This study aimed to explore medical students' learning experiences with virtual patient.

    METHODS: Ten students who previously underwent the learning module were recruited through purposive sampling. The inclusion criteria were: (a) Fourth-year medical students; and (b) Completed psychiatry posting with the new module. Students who dropped out or were unable to participate in data collection were excluded. Two online focus group discussions (FGDs) with five participants each were conducted by an independent facilitator, guided by a questioning route. The data were transcribed verbatim and coded using the thematic analysis approach to identify themes.

    RESULTS: Three main themes of their learning experience were identified: (1) fulfilment of the desired pedagogy (2), realism of the clinical case, and (3) ease of use related to technical settings. The pedagogy theme was further divided into the following subthemes: level of entry for students, flexibility of presentation of content, provision of learning guidance, collaboration with peers, provision of feedback, and assessment of performance. The realism theme had two subthemes: how much the virtual patient experience mimicked an actual patient and how much the case scenario reflected real conditions in the Malaysian context. The technical setting theme entailed two subthemes: access to the software and appearance of the user interface. The study findings are considered in the light of learning formats, pedagogical and learning theories, and technological frameworks.

    CONCLUSIONS: The findings shed light on both positive and negative aspects of using virtual patients for medical students' psychiatry posting, which opens room for further improvement of their usage in undergraduate psychiatry education.

    Matched MeSH terms: Learning
  10. Woon KL, Chong ZX, Ariffin A, Chan CS
    J Mol Graph Model, 2021 06;105:107891.
    PMID: 33765526 DOI: 10.1016/j.jmgm.2021.107891
    Fused tricyclic organic compounds are an important class of organic electronic materials. In designing molecules for organic electronics, knowing what chemical structure that be used to tune the molecular property is one of the keys that can help to improve the material performance. In this research, we applied machine learning and data analytic approaches in addressing this problem. The energy states (Lowest Unoccupied Molecular Orbital (HOMO), Highest Occupied Molecular Orbitals (LUMO), singlet (Es) and triplet (ET) energy) of more than 10 thousand fused tricyclics are calculated. Corresponding descriptors are also generated. We find that the Coulomb matrix is a poorer descriptor than high-level descriptors in a multilayer perceptron neural network. Correlations as high as 0.95 is obtained using a multilayer perceptron neural network with Mean Absolute Error as low as 0.08 eV. The descriptors that are important in tuning the energy levels are revealed using the Random Forest algorithm. Correlations of such descriptors are also plotted. We found that the higher the number of tertiary amines, the deeper are the HOMO and LUMO levels. The presence of NN in the aromatic rings can be used to tune the ES. However, there is no single dominant descriptor that can be correlated with the ET. A collection of descriptors is found to give a far better correlation with ET. This research demonstrated that machine learning and data analytics in guiding how certain chemical substructures correlate with the molecule energy states.
    Matched MeSH terms: Machine Learning*
  11. Woods C, Naroo S, Zeri F, Bakkar M, Barodawala F, Evans V, et al.
    Cont Lens Anterior Eye, 2023 Apr;46(2):101821.
    PMID: 36805277 DOI: 10.1016/j.clae.2023.101821
    INTRODUCTION: Evidence based practice is now an important part of healthcare education. The aim of this narrative literature review was to determine what evidence exists on the efficacy of commonly used teaching and learning and assessment methods in the realm of contact lens skills education (CLE) in order to provide insights into best practice. A summary of the global regulation and provision of postgraduate learning and continuing professional development in CLE is included.

    METHOD: An expert panel of educators was recruited and completed a literature review of current evidence of teaching and learning and assessment methods in healthcare training, with an emphasis on health care, general optometry and CLE.

    RESULTS: No direct evidence of benefit of teaching and learning and assessment methods in CLE were found. There was evidence for the benefit of some teaching and learning and assessment methods in other disciplines that could be transferable to CLE and could help students meet the intended learning outcomes. There was evidence that the following teaching and learning methods helped health-care and general optometry students meet the intended learning outcomes; clinical teaching and learning, flipped classrooms, clinical skills videos and clerkships. For assessment these methods were; essays, case presentations, objective structured clinical examinations, self-assessment and formative assessment. There was no evidence that the following teaching and learning methods helped health-care and general optometry students meet the intended learning outcomes; journal clubs and case discussions. Nor was any evidence found for the following assessment methods; multiple-choice questions, oral examinations, objective structured practical examinations, holistic assessment, and summative assessment.

    CONCLUSION: Investigation into the efficacy of common teaching and learning and assessment methods in CLE are required and would be beneficial for the entire community of contact lens educators, and other disciplines that wish to adapt this approach of evidence-based teaching.

    Matched MeSH terms: Learning*
  12. Wong ZY, Daher AM, Pathirage K, Lim KG
    Med Teach, 2023 Jul;45(7):789.
    PMID: 36705016 DOI: 10.1080/0142159X.2023.2169119
    Matched MeSH terms: Learning
  13. Wong WJ, Affendi NANM, Siow SL, Mahendran HA, Lau PC, Ho SH, et al.
    Surg Endosc, 2023 Mar;37(3):1735-1741.
    PMID: 36214914 DOI: 10.1007/s00464-022-09680-2
    INTRODUCTION: Per-Oral Endoscopic Myotomy (POEM) is an effective treatment for Esophageal Achalasia Cardia (EAC) but the endoscopic technique required is complex. As competency is crucial for patient safety, we believe that its' competency can be demonstrated when the complication rate equals that of an established procedure such as Laparoscopic Heller's Myotomy with Fundoplication (LHM + F).

    METHODS: A multicentre, ambi-directional, non-randomized comparison of intra-procedural complications during the learning curve of POEM was performed against a historical cohort of LHM + F. Demographic, clinicopathological, procedural data and complications were collected. A direct head-to-head comparison was performed, followed by a population pyramid of complication frequency. Case sequence was then divided into blocks of 5, and the complication rates during each block was compared to the historical cohort.

    RESULTS: From January 2010 to April 2021, 60 patients underwent LHM + F and 63 underwent POEM. Mean age was lower for the POEM group (41.7 years vs 48.1 years, p = 0.03), but there was no difference in gender nor type of Achalasia. The POEM group recorded a shorter overall procedural time (125.9 min vs 144.1 min, p = 0.023) and longer myotomies (10.1 cm vs 6.2 cm, p = 0.023). The overall complication rate of POEM was 20.6%, whereas the historical cohort of LHM + F had a rate of 10.0%. On visual inspection of the population pyramid, complications were more frequent in the earlier procedures. On block sequencing, complication frequency could be seen tapering off dramatically after the 25th case, and subsequently equalled that of LHM + F.

    CONCLUSION: POEM is challenging even for experienced endoscopists. From our data, complication rates between POEM and LHM + F equalize after approximately 25 POEMs.

    Matched MeSH terms: Learning Curve
  14. Wong WJ, Lee SWH, White PJ, Efendie B, Lee RFS
    Curr Pharm Teach Learn, 2023 Mar;15(3):242-251.
    PMID: 37055316 DOI: 10.1016/j.cptl.2023.03.004
    INTRODUCTION: To adapt to flipped classroom pedagogy in universities, factors such as the amount of the program that is flipped, students' pre-existing educational experiences, and cultural background may influence adjusting to the approach. We investigated students' perspectives across four years of a predominantly flipped classroom-based pharmacy curriculum in a low to middle income country.

    METHODS: We conducted five semi-structured focus groups with 18 pharmacy students from years one to four of the bachelor of pharmacy program at Monash University Malaysia where students came from different pre-university backgrounds. Focus group recordings were transcribed verbatim and thematically analysed. Interrater reliability was performed to ascertain reliability of themes.

    RESULTS: Three major themes were identified. Firstly, students cited issues moving past the initial barrier when starting flipped classrooms in terms of education background impacting adaptability and how/why they eventually adapted. Another theme was how flipped classrooms helped development of life skills such as adaptability, communication, teamwork, self-reflection, and time management. The final theme was on requiring a sufficient safety net and support system in flipped classrooms that included well designed pre-classroom materials and well-implemented feedback mechanisms.

    CONCLUSIONS: We have identified students' perspectives on the benefits and challenges associated with a predominantly flipped classroom pharmacy curriculum in a low to middle income country setting. We suggest using scaffolding and effective feedback approaches to guide the implementation of flipped classrooms successfully. This work can aid future educational designers in preparation and supporting a more equitable learning experience regardless of student background.

    Matched MeSH terms: Learning
  15. Wong RSY, Siow HL, Kumarasamy V, Shaherah Fadhlullah Suhaimi N
    J Adv Med Educ Prof, 2017 Oct;5(4):164-171.
    PMID: 28979910
    INTRODUCTION: The learner-centred approach in medical and health sciences education makes the study of learning preferences relevant and important. This study aimed to investigate the interdisciplinary, inter-institutional, gender and racial differences in the preferred learning styles among Malaysian medical and health sciences students in three Malaysian universities, namely SEGi University (SEGi), University of Malaya (UM) and Universiti Tunku Abdul Rahman (UTAR). It also investigated the differences in the preferred learning styles of these students between high achievers and non-high achievers.
    METHODS: This cross-sectional study was carried out on medical and health sciences students from three Malaysian universities following the approval of the Research and Ethics Committee, SEGi University. Purposive sampling was used and the preferred learning styles were assessed using the VARK questionnaire. The questionnaire was validated prior to its use. Three disciplines (medicine, pharmacy and dentistry) were chosen based on their entry criteria and some similarities in their course structure. The three participating universities were Malaysian universities with a home-grown undergraduate entry medical program and students from a diverse cultural and socioeconomic background. The data were analysed using the Statistical Package for the Social Sciences (SPSS) software, version 22. VARK subscale scores were expressed as mean+standard deviation. Comparisons of the means were carried out using t-test or ANOVA. A p value of <0.05 was considered as statistically significant, and <0.001 as highly significant.
    RESULTS: Both statistically significant interdisciplinary and inter-institutional differences in learning preferences were observed. Out of the 337 students, a majority of the participants were unimodal learners (n=263, 78.04%). The most common type of learners was the reading/writing type (n=92, 27.30%) while the kinesthetic subscale (M=6.98, SD=2.85) had the highest mean score. Female students (M=6.86, SD=2.86) scored significantly higher than male students (M=6.08, SD=2.41; t(249), p=0.014) in the auditory subscale, whereas Chinese students (M=5.87, SD=2.65) scored significantly higher than Malay students (M=4.70, SD=2.87; p=0.04) in the visual subscale. However, the mean VARK subscale scores did not differ significantly between high achievers and non-high achievers (p>0.05).
    CONCLUSION: This study gives an insight into the learner characteristics of more than one medical school in Malaysia. Such multi-institutional studies are lacking in the published literature and this study gives a better representation of the current situation in the learning preferences among medical students in Malaysia.
    Matched MeSH terms: Learning
  16. Wong N, Lee CY
    J Econ Entomol, 2010 Oct;103(5):1754-60.
    PMID: 21061976
    The aim of our study was to investigate the intra- and interspecific agonistic behaviors exhibited by the worker and soldier castes of the subterranean termite Microcerotermes crassus Snyder (Isoptera: Termitidae). Aggression between M. crassus colonies from different field locations and also against three termite species--Coptotermes gestroi (Wasmann), Globitermnes sulphureus Haviland, and Odontotermes sp.--were observed in the laboratory. Termite responses were tested in paired combination of castes (soldiers versus soldiers, soldiers versus workers, and workers versus workers) consisting of 10 individuals each. Significant agonistic behaviors were observed only in encounters between pairings of different termite species. M. crassus was aggressive toward individuals from different species but not toward individuals from different M. crassus colonies. Mortality of M. crassus reached 100% in most of the interspecific encounters. However, no or low mortality was recorded in the intraspecific pairings.
    Matched MeSH terms: Avoidance Learning
  17. Wolff GH, Riffell JA
    J Exp Biol, 2018 02 27;221(Pt 4).
    PMID: 29487141 DOI: 10.1242/jeb.157131
    Mosquitoes are best known for their proclivity towards biting humans and transmitting bloodborne pathogens, but there are over 3500 species, including both blood-feeding and non-blood-feeding taxa. The diversity of host preference in mosquitoes is exemplified by the feeding habits of mosquitoes in the genus Malaya that feed on ant regurgitation or those from the genus Uranotaenia that favor amphibian hosts. Host preference is also by no means static, but is characterized by behavioral plasticity that allows mosquitoes to switch hosts when their preferred host is unavailable and by learning host cues associated with positive or negative experiences. Here we review the diverse range of host-preference behaviors across the family Culicidae, which includes all mosquitoes, and how adaptations in neural circuitry might affect changes in preference both within the life history of a mosquito and across evolutionary time-scales.
    Matched MeSH terms: Learning
  18. Wirza R, Nazir S, Khan HU, García-Magariño I, Amin R
    J Healthc Eng, 2020;2020:8835544.
    PMID: 32963749 DOI: 10.1155/2020/8835544
    The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the activities of the mind and the human body. Modern speedy development in medical and computational growth in the field of the central nervous system enables practitioners and researchers to extract and visualize insight from these systems. The function of augmented reality is to incorporate virtual and real objects, interactively running in a real-time and real environment. The role of augmented reality in the central nervous system becomes a thought-provoking task. Gesture interaction approach-based augmented reality in the central nervous system has enormous impending for reducing the care cost, quality refining of care, and waste and error reducing. To make this process smooth, it would be effective to present a comprehensive study report of the available state-of-the-art-work for enabling doctors and practitioners to easily use it in the decision making process. This comprehensive study will finally summarise the outputs of the published materials associate to gesture interaction-based augmented reality approach in the central nervous system. This research uses the protocol of systematic literature which systematically collects, analyses, and derives facts from the collected papers. The data collected range from the published materials for 10 years. 78 papers were selected and included papers based on the predefined inclusion, exclusion, and quality criteria. The study supports to identify the studies related to augmented reality in the nervous system, application of augmented reality in the nervous system, technique of augmented reality in the nervous system, and the gesture interaction approaches in the nervous system. The derivations from the studies show that there is certain amount of rise-up in yearly wise articles, and numerous studies exist, related to augmented reality and gestures interaction approaches to different systems of the human body, specifically to the nervous system. This research organises and summarises the existing associated work, which is in the form of published materials, and are related to augmented reality. This research will help the practitioners and researchers to sight most of the existing studies subjected to augmented reality-based gestures interaction approaches for the nervous system and then can eventually be followed as support in future for complex anatomy learning.
    Matched MeSH terms: Machine Learning; Learning*
  19. Win NN, Nadarajah VD, Win DK
    PMID: 25961676 DOI: 10.3352/jeehp.2015.12.17
    PURPOSE: Problem-based learning (PBL) is usually conducted in small-group learning sessions with approximately eight students per facilitator. In this study, we implemented a modified version of PBL involving collaborative groups in an undergraduate chiropractic program and assessed its pedagogical effectiveness.
    METHODS: This study was conducted at the International Medical University, Kuala Lumpur, Malaysia, and involved the 2012 chiropractic student cohort. Six PBL cases were provided to chiropractic students, consisting of three PBL cases for which learning resources were provided and another three PBL cases for which learning resources were not provided. Group discussions were not continuously supervised, since only one facilitator was present. The students' perceptions of PBL in collaborative groups were assessed with a questionnaire that was divided into three domains: motivation, cognitive skills, and perceived pressure to work.
    RESULTS: Thirty of the 31 students (97%) participated in the study. PBL in collaborative groups was significantly associated with positive responses regarding students' motivation, cognitive skills, and perceived pressure to work (P<0.05). The students felt that PBL with learning resources increased motivation and cognitive skills (P<0.001).
    CONCLUSION: The new PBL implementation described in this study does not require additional instructors or any additional funding. When implemented in a classroom setting, it has pedagogical benefits equivalent to those of small-group sessions. Our findings also suggest that students rely significantly on available learning resources.
    KEYWORDS: Chiropractic; Learning; Motivation; Perception; Problem-based learning
    Matched MeSH terms: Problem-Based Learning*
  20. Widyahening IS, van der Heijden GJ, Moy FM, van der Graaf Y, Sastroasmoro S, Bulgiba A
    Perspect Med Educ, 2012 Dec;1(5-6):249-61.
    PMID: 23240103 DOI: 10.1007/s40037-012-0029-9
    Clinical epidemiology (CE) and evidence-based medicine (EBM) have become an important part of medical school curricula. This report describes the implementation and some preliminary outcomes of an integrated CE and EBM module in the Faculty of Medicine Universitas Indonesia (UI), Jakarta and in the University of Malaya (UM) in Kuala Lumpur. A CE and EBM module, originally developed at the University Medical Center Utrecht (UMCU), was adapted for implementation in Jakarta and Kuala Lumpur. Before the start of the module, UI and UM staff followed a training of teachers (TOT). Student competencies were assessed through pre and post multiple-choice knowledge tests, an oral and written structured evidence summary (evidence-based case report, EBCR) as well as a written exam. All students also filled in a module evaluation questionnaire. The TOT was well received by staff in Jakarta and Kuala Lumpur and after adaptation the CE and EBM modules were integrated in both medical schools. The pre-test results of UI and UM were significantly lower than those of UMCU students (p 
    Matched MeSH terms: Learning
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