METHODS: A survey was distributed to medical students in three consecutive years: 2017-2019. The survey contains items regarding student perception of various types of blended learning techniques applied in the course. The survey was administered using i-Clicker; an interactive device that enables students to answer survey questions. Descriptive statistics were used to examine the perception of students on these blended learning dimensions investigated.
RESULTS: Seven-hundred and one student responded to the questionnaire (male; 69.5%, female 30.5%). Out of which, 59.1% of students found team interactions positively supported discussions and asked questions freely, and 48.1% expressed that working in groups facilitated their learning process. However, 56.0% of students chose face-to-face lectures as the most preferred class activities followed by discussion 23.8%. More than 78% of participants agree that online quizzes are good experience and enjoyable. Grade center where students can check for marks and attendance also received high perception (66.3%).
CONCLUSION: Introducing modified team-based and blended-learning are considered challenging, and therefore, investigating their perceptions can provide useful insights into how these methods could be used more effectively. The blended-learning technique is highly essential in teaching medical informatics to overcome challenges faced due to a large number of students and the need for various exposures to reach the course's learning goals. Moreover, it is noticed that students were engaged in face-to-face and online activities, furthermore, modified team-based learning reported facilitating learning and asking questions without embarrassment.
DISCUSSION: It is a set of various methodologies which are used to capture internal or external images of the human body and organs for clinical and diagnosis needs to examine human form for various kind of ailments. Computationally intelligent machine learning techniques and their application in medical imaging can play a significant role in expediting the diagnosis process and making it more precise.
CONCLUSION: This review presents an up-to-date coverage about research topics which include recent literature in the areas of MRI imaging, comparison with other modalities, noise in MRI and machine learning techniques to remove the noise.
METHODS: Two overlapping cohorts of adults who reported smoking factory- made cigarettes from Malaysia and Thailand were interviewed face-to-face (3189 were surveyed at baseline and 1781 re-contacted at Wave 2; 2361 current smokers were surveyed at Wave 2 and 1586 re-contacted at Wave 3). In Thailand at baseline, large text only warnings were assessed, while at Wave 2 new large graphic warnings were assessed. In Malaysia, during both waves small text only warnings were in effect. Reactions were used to predict interest in quitting, and to predict making quit attempts over the following inter-wave interval.
RESULTS: Multivariate predictors of "interest in quitting" were comparable across countries, but predictors of quit attempts varied. In both countries, cognitive reactions to warnings (adjusted ORs; 1.57 & 1.69 for Malaysia at wave 1 and wave 2 respectively and 1.29 & 1.19 for Thailand at wave 1 and wave 2 respectively), forgoing a cigarette (except Wave 2 in Malaysia) (adjusted ORs; 1.77 for Malaysia at wave 1 and 1.54 & 2.32 for Thailand at wave 1 and wave 2 respectively), and baseline knowledge (except wave 2 in both countries) (adjusted ORs; 1.71 & 1.51 for Malaysia and Thailand respectively) were positively associated with interest in quitting at that wave. In Thailand only, "cognitive reactions to warnings" (adjusted ORs; 1.12 & 1.23 at wave 1 and wave 2 respectively), "forgoing a cigarette" (adjusted OR = 1.55 at wave 2 only) and "an interest in quitting" (adjusted ORs; 1.61 & 2.85 at wave 1 and wave 2 respectively) were positively associated with quit attempts over the following inter-wave interval. Salience was negatively associated with subsequent quit attempts in both Malaysia and Thailand, but at Wave 2 only (adjusted ORs; 0.89 & 0.88 for Malaysia and Thailand respectively).
CONCLUSION: Warnings appear to have common mechanisms for influencing quitting regardless of warning strength. The larger and more informative Thai warnings were associated with higher levels of reactions predictive of quitting and stronger associations with subsequent quitting, demonstrating their greater potency.
METHOD: For 293 consecutive patients admitted to our hospital via the emergency department for COVID-19 between 01/03/20 -18/05/20, demographic data, laboratory findings, admission electrocardiograph and clinical observations were compared in those who survived and those who died within 6 weeks. Hospital records were reviewed for prior electrocardiograms for comparison with those recorded on presentation with COVID-19.
RESULTS: Patients who died were older than survivors (82 vs 69.8 years, p 455 ms (males) and >465 ms (females) (p = 0.028, HR 1.49 [1.04-2.13]), as predictors of mortality. QTc prolongation beyond these dichotomy limits was associated with increased mortality risk (p = 0.0027, HR 1.78 [1.2-2.6]).
CONCLUSION: QTc prolongation occurs in COVID-19 illness and is associated with poor outcome.