Displaying publications 61 - 80 of 909 in total

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  1. Rusnani Ab Latif
    MyJurnal
    Introduction: The effectiveness of teaching and learning process is highly dependent on the methods and
    strategies of teaching and learning practices. As a result, nurse educator must choose and use the suitable
    method to help the nursing students to achieve the learning objective.

    Methodology: There were 218 respondents. This study consisted of two-group quasi experimental study
    with pre- and post-test design. The experimental and control groups received education using concept
    mapping and lecture method respectively. The data was analyzed using inferential and descriptive statistic.

    Results: In the pre-test, students were taught using concept mapping. These students had achievement
    mean scores of 11.23, SD=2.59 and post–test was 13.19, SD=1.71 with mean gain scores of 1.96. Students
    who were taught using lecture method had an achievement mean scores of 10.71, SD=2.23 in the pre-test
    and post-test was 12.60, SD=1.64 with mean gain scores of 1.89. The results showed an increase in grade
    achievement, the percentage pass for the experimental group increased from 95.4% in pre-test to 100% in
    the post-test. The percentage pass for control group had increased from 93.57% in pre-test increased to
    99.08% in the post-test.

    Conclusion: Student-centered learning is a teaching method that is active and can change passive to active
    learning. Findings from several reviewed studies suggest that using concept mapping can improve
    academic performance in nursing education and is a valuable teaching strategy.
    Matched MeSH terms: Learning
  2. Azer SA
    Kaohsiung J. Med. Sci., 2009 May;25(5):240-9.
    PMID: 19502144 DOI: 10.1016/S1607-551X(09)70068-3
    Problem-based learning (PBL) is an excellent opportunity for students to take responsibility for their learning and to develop a number of cognitive skills. These include identifying problems in the trigger, generating hypotheses, constructing mechanisms, developing an enquiry plan, ranking their hypotheses on the basis of available evidence, interpreting clinical and laboratory findings, identifying their learning needs, and dealing with uncertainty. Students also need to work collaboratively in their group, communicate effectively, and take active roles in the tutorials. Therefore, interaction in the group between students and their tutor is vital to ensure deep learning and successful outcomes. The aims of this paper are to discuss the key principles for successful interaction in PBL tutorials and to highlight the major symptoms of superficial learning and poor interactions. This comprises a wide range of symptoms for different group problems, including superficial learning. By early detection of such problems, tutors will be able to explore actions with the group and negotiate changes that can foster group dynamics and enforce deep learning.
    Matched MeSH terms: Learning; Problem-Based Learning*
  3. Azer SA
    Kaohsiung J. Med. Sci., 2009 Mar;25(3):109-15.
    PMID: 19419915 DOI: 10.1016/S1607-551X(09)70049-X
    Lectures are of great value to students. However, with the introduction of hybrid problem-based learning (PBL) curricula into most medical schools, the emphasis on lectures has decreased. This paper discusses how lectures can be used in a PBL curriculum, what makes a great lecture, and how to deliver a lecture that fits with these changes.
    Matched MeSH terms: Problem-Based Learning*
  4. Azer SA
    Kaohsiung J. Med. Sci., 2008 Jul;24(7):361-6.
    PMID: 18805751 DOI: 10.1016/S1607-551X(08)70133-5
    Portfolios have been used in the medical curriculum to evaluate difficult-to-assess areas such as students' attitudes, professionalism and teamwork. However, their use early in a problem-based learning (PBL) course to foster deep learning and enhance students' self-directed learning has not been adequately studied. The aims of this paper are to: (1) understand the uses of portfolios and the rationale for using reflection in the early years of a PBL curriculum; (2) discuss how to introduce portfolios and encourage students' critical thinking skills, not just reflection; and (3) provide students with tips that could enhance their skills in constructing good portfolios.
    Matched MeSH terms: Learning*; Problem-Based Learning*
  5. Tiang N, Ahad MA, Murugaiyah V, Hassan Z
    J Pharm Pharmacol, 2020 Nov;72(11):1629-1644.
    PMID: 32743849 DOI: 10.1111/jphp.13345
    OBJECTIVES: Xanthones isolated from the pericarp of Garcinia mangostana has been reported to exhibit neuroprotective effect.

    METHODS: In this study, the effect of xanthone-enriched fraction of Garcinia mangostana (XEFGM) and α-mangostin (α-MG) were investigated on cognitive functions of the chronic cerebral hypoperfusion (CCH) rats.

    KEY FINDINGS: HPLC analysis revealed that XEFGM contained 55.84% of α-MG. Acute oral administration of XEFGM (25, 50 and 100 mg/kg) and α-MG (25 and 50 mg/kg) before locomotor activity and Morris water maze (MWM) tests showed no significant difference between the groups for locomotor activity.

    CONCLUSIONS: However, α-MG (50 mg/kg) and XEFGM (100 mg/kg) reversed the cognitive impairment induced by CCH in MWM test. α-MG (50 mg/kg) was further tested upon sub-acute 14-day treatment in CCH rats. Cognitive improvement was shown in MWM test but not in long-term potentiation (LTP). BDNF but not CaMKII was found to be down-regulated in CCH rats; however, both parameters were not affected by α-MG. In conclusion, α-MG ameliorated learning and memory deficits in both acute and sub-acute treatments in CCH rats by improving the spatial learning but not hippocampal LTP. Hence, α-MG may be a promising lead compound for CCH-associated neurodegenerative diseases, including vascular dementia and Alzheimer's disease.

    Matched MeSH terms: Spatial Learning/drug effects*
  6. Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, et al.
    J Pathol, 2023 Aug;260(5):498-513.
    PMID: 37608772 DOI: 10.1002/path.6155
    The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
    Matched MeSH terms: Machine Learning
  7. 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
  8. Cheng TC, Yahya MFN, Mohd Naffi AA, Othman O, Seng Fai T, Yong MH, et al.
    J Craniofac Surg, 2021 Oct 01;32(7):2285-2291.
    PMID: 33770023 DOI: 10.1097/SCS.0000000000007645
    BACKGROUND: To evaluate the satisfaction of surgeons and trainees with three-dimensional (3D) ophthalmic surgery during a demonstration compared to traditional surgery.

    METHODS: This validated questionnaire-based study was conducted over 1-month during which Ngenuity 3D surgery was demonstrated. All surgeons and trainees exposed were recruited to complete a questionnaire comprising visualization, physical, ease of use, teaching and learning, and overall satisfaction.

    RESULTS: All 7 surgeons and 33 postgraduate students responded. Surgeons reported no significant difference except overall (P = 0.047, paired t-test). Postgraduate trainees reported significantly better experience with 3D for illumination (P = 0.008), manoeuvrability (P = 0.01), glare (P = 0.037), eye strain (P = 0.008), neck and upper back strain (P = 0.000), lower back pain (P = 0.019), communication (P = 0.002), comfortable environment (P = 0.001), sharing of knowledge (P = 0.000), and overall (P = 0.009).

    CONCLUSIONS: During early experience, surgeons and trainees reported better satisfaction with 3D overall. Trainees had better satisfaction with 3D in various subcomponents of visualization, physical, ease of use, and education.

    Matched MeSH terms: Learning
  9. Prabhu GS, K G Rao M, Rai KS
    Int J Neurosci, 2021 Nov;131(11):1066-1077.
    PMID: 32498586 DOI: 10.1080/00207454.2020.1773819
    PURPOSE: Childhood obesity increases risk for neural dysfunctions causing learning and memory deficits. The objective of the study is to identify the effects of high fat diet-induced obesity in postnatal period on serum lipids, memory and neural cell survival in hippocampus and compare the role of choline and DHA or environmental enrichment in attenuating the alterations.

    MATERIALS AND METHODS: 21 day postnatal male Sprague Dawley rats were assigned as Normal control [NC] fed normal chow diet, Obesity-induced [OB] fed high fat diet, Obesity-induced fed choline & DHA [OB + CHO + DHA], Obesity-induced environmental enrichment [OB + EE] [n = 8/group]. Memory was assessed using radial arm maze. Subsequently blood was collected for serum lipid analysis and rats were euthanized. 5 µm hippocampal sections were processed for cresyl-violet stain. Surviving neural cells were counted using 100 µm scale.

    RESULTS: Memory errors were significantly higher [p 

    Matched MeSH terms: Maze Learning/physiology
  10. Salowi MA, Choong YF, Goh PP, Ismail M, Lim TO
    Br J Ophthalmol, 2010 Apr;94(4):445-9.
    PMID: 19951939 DOI: 10.1136/bjo.2009.163063
    AIMS: To apply cumulative sum (CUSUM) in monitoring performance of surgeons in cataract surgery and to evaluate the response of performance to intervention.
    METHOD: A CUSUM analysis was applied to 80 phacoemulsification performed by three ophthalmic trainees and one consultant, for the occurrence of posterior capsular rupture and postoperative refracted vision of worse than 6/12 among patients without pre-existing ocular comorbidity. The CUSUM score of each consecutive procedure performed by an individual surgeon was calculated and charted on CUSUM chart. When trainees' CUSUM charts showed an unacceptable level of performance, their supervisors would give feedback and impose closer monitoring of subsequent surgeries.
    RESULTS: CUSUM charts of the trainees demonstrated an initial upward followed by flattening trend. This reflects learning curves in their process of acquiring competency in phacoemulsification. In contrast, the consultant showed a flat curve indicating an ongoing maintenance of competence.
    CONCLUSION: The CUSUM analysis is able to monitor and promptly detect adverse events and trends of unacceptable outcomes in cataract surgery. This objective and dynamic monitoring makes CUSUM a useful audit tool for individual surgeons, but more so for busy consultants who need to supervise trainees.
    Matched MeSH terms: Learning Curve*
  11. Al-Mekhlafi HM, Mahdy MA, Sallam AA, Ariffin WA, Al-Mekhlafi AM, Amran AA, et al.
    Br J Nutr, 2011 Oct;106(7):1100-6.
    PMID: 21492493 DOI: 10.1017/S0007114511001449
    A community-based cross-sectional study was carried out among Aboriginal schoolchildren aged 7-12 years living in remote areas in Pos Betau, Pahang, Malaysia to investigate the potential determinants influencing the cognitive function and educational achievement of these children. Cognitive function was measured by intelligence quotient (IQ), while examination scores of selected school subjects were used in assessing educational achievement. Blood samples were collected to assess serum Fe status. All children were screened for soil-transmitted helminthes. Demographic and socio-economic data were collected using pre-tested questionnaires. Almost two-thirds (67·6 %) of the subjects had poor IQ and most of them (72·6 %) had insufficient educational achievement. Output of the stepwise multiple regression model showed that poor IQ was significantly associated with low household income which contributed the most to the regression variance (r2 0·059; P = 0·020). Low maternal education was also identified as a significant predictor of low IQ scores (r2 0·042; P = 0·043). With educational achievement, Fe-deficiency anaemia (IDA) was the only variable to show significant association (r2 0·025; P = 0·015). In conclusion, the cognitive function and educational achievement of Aboriginal schoolchildren are poor and influenced by household income, maternal education and IDA. Thus, effective and integrated measures to improve the nutritional and socio-economic status of rural children would have a pronounced positive effect on their education.
    Matched MeSH terms: Learning*
  12. Smith SN
    Br J Educ Psychol, 2001 Sep;71(Pt 3):429-41.
    PMID: 11593949
    Although numerous studies have examined the learning approaches of Chinese students, very few comparative studies have been carried out with Chinese students from different nations.
    Matched MeSH terms: Learning
  13. El-Badawy IM, Singh OP, Omar Z
    Technol Health Care, 2021;29(1):59-72.
    PMID: 32716337 DOI: 10.3233/THC-202198
    BACKGROUND: The quantitative features of a capnogram signal are important clinical metrics in assessing pulmonary function. However, these features should be quantified from the regular (artefact-free) segments of the capnogram waveform.

    OBJECTIVE: This paper presents a machine learning-based approach for the automatic classification of regular and irregular capnogram segments.

    METHODS: Herein, we proposed four time- and two frequency-domain features experimented with the support vector machine classifier through ten-fold cross-validation. MATLAB simulation was conducted on 100 regular and 100 irregular 15 s capnogram segments. Analysis of variance was performed to investigate the significance of the proposed features. Pearson's correlation was utilized to select the relatively most substantial ones, namely variance and the area under normalized magnitude spectrum. Classification performance, using these features, was evaluated against two feature sets in which either time- or frequency-domain features only were employed.

    RESULTS: Results showed a classification accuracy of 86.5%, which outperformed the other cases by an average of 5.5%. The achieved specificity, sensitivity, and precision were 84%, 89% and 86.51%, respectively. The average execution time for feature extraction and classification per segment is only 36 ms.

    CONCLUSION: The proposed approach can be integrated with capnography devices for real-time capnogram-based respiratory assessment. However, further research is recommended to enhance the classification performance.

    Matched MeSH terms: Machine Learning
  14. Ahmad RF, Malik AS, Kamel N, Reza F, Amin HU, Hussain M
    Technol Health Care, 2017;25(3):471-485.
    PMID: 27935575 DOI: 10.3233/THC-161286
    BACKGROUND: Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful.

    METHODS: In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes.

    RESULTS: Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature.

    CONCLUSIONS: The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

    Matched MeSH terms: Machine Learning
  15. Ali M, Wahab IBA, Huri HZ, Yusoff MS
    Syst Rev, 2024 Apr 02;13(1):99.
    PMID: 38566190 DOI: 10.1186/s13643-024-02478-4
    BACKGROUND: Personalised learning, an educational approach that tailors teaching and learning to individual needs and preferences, has gained attention in recent years, particularly in higher education. Advances in educational technology have facilitated the implementation of personalised learning in various contexts. Despite its potential benefits, the literature on personalised learning in health sciences higher education remains scattered and heterogeneous. This scoping review aims to identify and map the current literature on personalised learning in health sciences higher education and its definition, implementation strategies, benefits, and limitations.

    METHODS: A comprehensive search of electronic databases, PubMed, Scopus, Google Scholar, Educational Research Complete, and Journal Storage (JSTOR), will be conducted to identify relevant articles. The search will be limited to articles published in the English language between 2000 and 2023. The search strategy will be designed and adapted for each database using a combination of keywords and subject headings related to personalised learning and health sciences higher education. Eligibility criteria will be applied to screen and select articles. Data extraction and quality assessment will be performed, and thematic synthesis will be used to analyse the extracted data.

    DISCUSSION: The results of the scoping review will present a comprehensive and coherent overview of the literature on personalised learning in health sciences higher education. Key themes and topics related to personalised learning, its definitions, models, implementation strategies, benefits, and limitations, will be identified. The geographical and temporal distribution of research on personalised learning in health sciences higher education will also be described. This scoping review will provide a structured synthesis of the available evidence on personalised learning in health sciences higher education, highlighting potential gaps and areas for future research. The findings will contribute to ongoing scholarly and policy debates on personalised learning in higher education, informing the development of best practices, guidelines, and future research agendas.

    Matched MeSH terms: Learning*
  16. 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
  17. Mustafa AG, Allouh MZ, Mustafa IG, Hoja IM
    Surg Radiol Anat, 2013 Jul;35(5):435-41.
    PMID: 23292088 DOI: 10.1007/s00276-012-1067-z
    The study aims to investigate anatomy learning styles and strategies of Jordanian and Malaysian medical students at the Jordan University of Science and Technology.
    Matched MeSH terms: Learning
  18. Cheah YN, Rashid FA, Abidi SS
    PMID: 14664077
    Existing Problem-Based Learning (PBL) problems, though suitable in their own right for teaching purposes, are limited in their potential to evolve by themselves and to create new knowledge. Presently, they are based on textbook examples of past cases and/or cases that have been transcribed by a clinician. In this paper, we present (a) a tacit healthcare knowledge representation formalism called Healthcare Scenarios, (b) the relevance of healthcare scenarios in PBL in healthcare and medicine, (c) a novel PBL-Scenario-based tacit knowledge explication strategy and (d) an online PBL Problem Composer and Presenter (PBL-Online) to facilitate the acquisition and utilisation of expert-quality tacit healthcare knowledge to enrich online PBL. We employ a confluence of healthcare knowledge management tools and Internet technologies to bring tacit healthcare knowledge-enriched PBL to a global and yet more accessible level.
    Matched MeSH terms: Problem-Based Learning*
  19. Chan CYW, Lee SY, Ch'ng PY, Chung WH, Chiu CK, Hasan MS, et al.
    Spine (Phila Pa 1976), 2021 Jun 15;46(12):E663-E670.
    PMID: 33306608 DOI: 10.1097/BRS.0000000000003866
    STUDY DESIGN: Retrospective study.

    OBJECTIVE: To assess the learning curve of a dual attending surgeon strategy in severe adolescent idiopathic scoliosis patients.

    SUMMARY OF BACKGROUND DATA: The advantages of a dual attending surgeon strategy in improving the perioperative outcome in scoliosis surgery had been reported. However, the learning curve of this strategy in severe scoliosis had not been widely studied.

    METHODS: A total of 105 patients with adolescent idiopathic scoliosis with Cobb angle of 90° or greater, who underwent posterior spinal fusion using a dual attending surgeon strategy were recruited. Primary outcomes were operative time, total blood loss, allogeneic blood transfusion requirement, length of hospital stay from time of operation and perioperative complications. Cases were sorted chronologically into group 1: cases 1 to 35, group 2: cases 36 to 70, and group 3: case 71 to 105. Mean operative time (≤193.3 min), total blood loss (≤1612.2 mL), combination of both and allogeneic blood transfusion were the selected criteria for receiver operating characteristic analysis of the learning curve.

    RESULTS: The mean Cobb angle was 104.5° ± 12.3°. The operative time, total blood loss, and allogeneic blood transfusion requirement reduced significantly for group 1 (220.6 ± 54.8 min; 2011.3 ± 881.8 mL; 12 cases) versus group 2 (183.6 ± 36.7 min; 1481.6 ± 1035.5 mL; 3 cases) and group 1 versus group 3 (175.6 ± 38.4 min; 1343.7 ± 477.8 mL; 3 cases) (P 

    Matched MeSH terms: Learning Curve
  20. Yoon TL, Yeap ZQ, Tan CS, Chen Y, Chen J, Yam MF
    PMID: 34627017 DOI: 10.1016/j.saa.2021.120440
    A proof-of-concept medicinal herbs identification scheme using machine learning classifiers is proposed in the form of an automated computational package. The scheme makes use of two-dimensional correlation Fourier Transformed Infrared (FTIR) fingerprinting maps derived from the FTIR of raw herb spectra as digital input. The prototype package admits a collection of 11 machine learning classifiers to form a voting pool. A common set of oversampled dataset containing 5 different herbal classes is used to train the pool of classifiers on a one-verses-others manner. The collections of trained models, dubbed the voting classifiers, are deployed in a collective manner to cast their votes to support or against a given inference fingerprint whether it belongs to a particular class. By collecting the votes casted by all voting classifiers, a logically designed scoring system will select out the most probable guess of the identity of the inference fingerprint. The same scoring system is also capable of discriminating an inference fingerprint that does not belong to any of the classes the voting classifiers are trained for as the 'others' type. The proposed classification scheme is stress-tested to evaluate its performance and expected consistency. Our experimental runs show that, by and large, a satisfactory performance of the classification scheme of up to 90 % accuracy is achieved, providing a proof-of-concept viability that the proposed scheme is a feasible, practical, and convenient tool for herbal classification. The scheme is implemented in the form of a packaged Python code, dubbed the "Collective Voting" (CV) package, which is easily scalable, maintained and used in practice.
    Matched MeSH terms: Machine Learning
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