A comparative study of teaching anatomy using cadavers, prosected wet specimens and simulated plastic models among Malaysian undergraduates

It is a challenge that the dissecting room still has a place in teaching gross anatomy. Understanding the students’ perceptions and experiences of learning anatomy is important to get sound knowledge of the human body. This study was conducted to assess which teaching aid would facilitate students’ understanding of the human body in order to get a more evidence – based approach to clinical anatomy. A cross – sectional comparative study was carried out among 741 medical and dental students of International Islamic University Malaysia (IIUM), Universiti Teknologi MARA (UiTM), University Sabah Malaysia (USM) and University Malaysia Sarawak (UNIMAS). A pre-tested, semi-structured, self administrated questionnaire which includes open–ended questions was distributed to collect the data on handability, understanding, information, application and preference. The data was analysed using chi-square test at “α“ 0.05 (SPSS version 17). The students from IIUM, UiTM, USM and UNIMAS scored the highest preference for plastic models on handability and application in examination (OSPE). It was statistically significant (p0.05) in USM (information and application in OSPE) and UNIMAS (understanding and information). The overall preference for students of IIUM and UiTM was the plastic models (85.8% and 44.1% respectively) while for UNIMAS the prosected wet specimens (90.7%) followed by plastic models (87.8%). USM students mostly preferred the cadavers (51.9%) followed by plastic models (50%). These inter-universities differences were statistically significant (p<0.05). This study suggests that the plastic model can fit very well into the structure of modern medical training and therefore improve the teaching of anatomy in surgical specialities

Preference in learning gross anatomy among IIUM students

Both medical (Year I, Year II) and dental (Year I) students in IIUM are exposed to three types of teaching aids in learning gross anatomy. They are cadavers, prosected wet specimens and plastic models. This study aimed at exploring the students’ preference on teaching aids in learning gross anatomy and reasons for their preference. A cross-sectional comparative study was carried out among 185 medical and dental students by using the pretested, semi structured, self administrated questionnaires including open-ended questions. Significance of preferences were analysed by X2 test. Year I (99%) and Year II (97%) medical students preferred the plastic models as the best approach to learn gross anatomy because of their handleability and portability. Year I dental students (96%) preferred the prosected wet specimens because they were real human structures and well preserved. The preferred and less preferred rates were 86% and 4% for plastic model, 84% and 10% for prosected wet specimen and 77% and 17% for cadaver. These differences were statistically significant (p <0.05). Students didn’t prefer the cadavers most but they agreed that the cadavers are more realistic, informative and easier to remember. This study indicates that students prefer all three types of teaching aids while the most preferred one is the plastic model. The quality of teaching aid is the reason for their preference. Students’ suggestion to use the advanced technologies such as three dimensional animations or simulated videos should be considered to get discernable learning outcomes

Anaphora Resolution for Myanmar Text Using K-Nearest Neighbor Algorithm

Anaphora resolution which most commonly appears as pronoun resolution is the problem of resolving references to earlier or later items in the discourse. Anaphora resolution is an active area of research, such as text mining, text summarization, dialogue interpretations, information extraction, and so on. Anaphora resolution in English and other European languages has been well done in early. But Myanmar Language has not sufficiently applied. This paper presents Myanmar anaphora resolution system by using rule-based part of speech tagging and machine learning approach. Rule-based manner with morphological informat ion is used to collect anaphora and possible antecedents. K-Nearest Neighbor (k-NN) approach is used to select the most probable candidate as the antecedent of the anaphor

ADVANCE: Towards near real-time monitoring of vaccination coverage, benefits and risks using European electronic health record databases

BACKGROUND: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private partnership aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using European electronic health record (eHR) databases. This proof-of-concept study aimed to test the feasibility of near real-time (NRT) monitoring of vaccination coverage, benefits and risks based on multiple European eHR databases, using acellular pertussis vaccination in children aged <6 years as test case. METHODS: A qualitative feasibility assessment on NRT monitoring was carried out using a survey and face-to-face discussion with ADVANCE data partners. Subsequently, a dynamic cohort study was conducted containing two distinct observation periods: a first period to establish a baseline (Jan 2014 to Mar 2018) and a subsequent 3-month period to test the actual feasibility of weekly NRT monitoring, based on which data latencies were calculated. An interactive web-application was additionally developed to facilitate the visual monitoring of vaccination coverage, the vaccine preventable disease incidence rates (benefits) and the incidence rates of adverse events (risks). RESULTS: Nine databases from four countries (Denmark, Italy, Spain and UK) participated in the qualitative feasibility assessment. Of them, five databases took part in the dynamic cohort study, with 5 databases providing baseline data and 3 databases participating to the NRT monitoring, providing data extractions on an almost weekly basis. The median data latency (time between event date and data release date) was between 1 and 2 weeks except for the benefit and risk events in one of the databases (latency 16 weeks). CONCLUSION: Three European eHR databases successfully demonstrated the feasibility of providing data for weekly NRT monitoring, with short data latencies of 1-2 weeks for most events

Advance system testing: Vaccine benefit studies using multi-country electronic health data – The example of pertussis vaccination

The Accelerated Development of VAccine benefit-risk Collaboration in Europe (ADVANCE), a public-private consortium, implemented and tested a distributed network system for the generation of evidence on the benefits-risks of marketed vaccines in Europe. We tested the system by estimating the incidence rate (IR) of pertussis and pertussis-related complications in children vaccinated with acellular (aP) and whole-cell (wP) pertussis vaccine. Data from seven electronic databases from four countries (Denmark: AUH and SSI, Spain: SIDIAP and BIFAP, UK: THIN and RCGP RSC and Italy: Pedianet) were included in a retrospective cohort analysis. Exposure was defined as any pertussis vaccination (aP or wP). The follow-up time started 14 days after the first dose. Children who had received any pertussis vaccine from January 1990 to December 2015 were included (those w

"Un pèlerinage", traduction et édition d'une nouvelle birmane de U Hpo Kya (1937)

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Implementation of Case-based Reasoning System for Criminal Judgement

Case-Based Reasoning (CBR) is theprocess of solving new problems based on thesolutions of similar past problems. The CBR canbe used to find the specific knowledge ofpreviously experienced problem situations(cases).The purpose of this system is to develop acase-based reasoning system for criminaljudgment. A new problem is solved by finding asimilar past case, and reusing it in the newproblem situation. CBR is also an approach toincremental, sustained learning because a newexperience is retained each time a problem hasbeen solved, making it immediately available forfuture problems. By using the knowledge of expertand documentation, this system applies four tasksof CBR for criminal judgements. The systemproduces the judgment or punishment as caseoutput. The system can also retain the successfulcase solutions for future assistance

Myanmar-English Bidirectional Machine Translation System by Using Transfer Based Approach

This paper presents the development ofbidirectional machine translation system of Myanmar-English. This Machine Translation system is based onTransfer Based Approach. It contains three stages: (1)source sentence analysis stages, (2) the structure ofsource sentence to the structure of target sentencetransferstages and (3) target sentence generationstages.In the analysis stage, input source sentence isparsed with the help of existing parsers. To changefrom source sentence structure to target sentencestructure, tree to tree transformation approach isapplied by using Synchronous Context Free Grammar(SCFG) rules. Morphological synthesis is alsoconsidered to improve smooth translationin thegeneration stage because Myanmar language isamorphologically rich language