Online Medical Education in India – Different Challenges and Probable Solutions in the Age of COVID-19

Nimavat, Nirav; Singh, Shruti; Fichadiya, Nilesh; Sharma, Parul; Patel, Nilesh; Kumar, Manoj; Chauhan, Grishma; Pandit, Niraj

doi:10.2147/amep.s295728

Cited by 130 publications

(130 citation statements)

References 23 publications

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“…For example, if most points occur above or below the axis y = 0, it indicates a computational bias (over or underestimation) in one of the two methods. In contrast, a homogeneous distribution of data around the line y = 0 shows consistency between measures obtained with the two methods and the agreement measured ( Giavarina, 2015 ; Kalra, 2017 ). Analyses were made with SPSS Statistics 20.0 (IBM Corp., Armonk, NY, United States).…”

Section: Methodssupporting

confidence: 69%

A Validation of Supervised Deep Learning for Gait Analysis in the Cat

Lecomte

Audet

Harnie

et al. 2021

Front. Neuroinform.

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Gait analysis in cats and other animals is generally performed with custom-made or commercially developed software to track reflective markers placed on bony landmarks. This often involves costly motion tracking systems. However, deep learning, and in particular DeepLabCutTM (DLC), allows motion tracking without requiring placing reflective markers or an expensive system. The purpose of this study was to validate the accuracy of DLC for gait analysis in the adult cat by comparing results obtained with DLC and a custom-made software (Expresso) that has been used in several cat studies. Four intact adult cats performed tied-belt (both belts at same speed) and split-belt (belts operating at different speeds) locomotion at different speeds and left-right speed differences on a split-belt treadmill. We calculated several kinematic variables, such as step/stride lengths and joint angles from the estimates made by the two software and assessed the agreement between the two measurements using intraclass correlation coefficient or Lin’s concordance correlation coefficient as well as Pearson’s correlation coefficients. The results showed that DLC is at least as precise as Expresso with good to excellent agreement for all variables. Indeed, all 12 variables showed an agreement above 0.75, considered good, while nine showed an agreement above 0.9, considered excellent. Therefore, deep learning, specifically DLC, is valid for measuring kinematic variables during locomotion in cats, without requiring reflective markers and using a relatively low-cost system.

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Section: Methodssupporting

confidence: 69%

A Validation of Supervised Deep Learning for Gait Analysis in the Cat

Lecomte

Audet

Harnie

et al. 2021

Front. Neuroinform.

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“…Therefore, based on these results and hemolytic activity, these 3 isolates were selected for antibiotic susceptibility evaluation. The antibiotic susceptibility results of isolated LAB against nine clinically important and widely used antibiotics in Iran are presented in Table 5 ( Abbasian et al, 2019 ). All three isolates were sensitive or semi-sensitive to cefixime, azithromycin, amoxicillin, doxycycline, cephalexin, and amoxicillin-clavulanic acid.…”

Section: Resultsmentioning

confidence: 99%

Application of Tarkhineh Fermented Product to Produce Potato Chips With Strong Probiotic Properties, High Shelf-Life, and Desirable Sensory Characteristics

et al. 2021

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The application of Tarkhineh texture to protect probiotics in potato chips has been investigated as the main goal in this paper. In this study, the probiotic assessments, morphological characteristics, sensory evaluation, and survival rates of the covered probiotic cells with Tarkhineh in potato chips during storage time were assessed. Based on results, T34 isolated from traditional Tarkhineh as a safe strain had a high tolerance to low pH and bile salt conditions, displayed acceptable anti-pathogenic activities, and also showed desirable antibiotic susceptibility. Two types of Tarkhineh formulations (plain Tarkhineh and turmeric Tarkhineh) were applied using a simple spraying method for covering T34 cells in potato chips. All formulations showed elliptical to spherical (480-770 μm) shape probiotic drops. Storage stability results revealed that T34 cells mixed with turmeric and plain Tarkhineh during 4 months of storage at 4°C displayed excellent protection abilities with about 3.70 and 2.85 log decreases in CFU/g respectively. Additionally, probiotic potato chips compared to non-probiotic and commercial potato chips, exhibited probiotic product criteria such as excellent quality and superior sensory properties during storage time. In conclusion, Tarkhineh showed high potential as a protective matrix for probiotic cells in potato chips.

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“…When it comes to implementing online medical education, infrastructure, including learning equipment and Internet connection, was one of the major challenges in developing countries. 8 However, that challenge was the original one for medical students learning online in China and was soon replaced as the issue was fixed in a short time. The operation of online learning websites and apps took tremendous pressure because the whole country started online education overnight, which generated numerous pressure on servers.…”

Section: Discussionmentioning

confidence: 99%

Students’ and Teachers’ Perspective on the Implementation of Online Medical Education in China: A Qualitative Study

Wang¹,

Yu²,

Liu³

et al. 2021

AMEP

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Objective Due to the quarantine measures during the outbreak of COVID-19, medical schools in China had to shift to online education overnight. Researchers wanted to survey the online medical education status quo and find out the underlying challenges and probable solutions in terms of online medical education to better understand improving and developing medical education in China. Methods Researchers distributed self-administered and piloted surveys regarding the implementation of online medical education on WeChat and Wenjuanxing. Researchers distributed three phases of online surveys to the undergraduate medical students, and one online survey to the medical teachers on phase three. Results Online medical education was carried out smoothly in China. Seventy-six percent of the students were satisfied with online medical education, and it hardly changed after a month. Courses with the quiz and live-stream courses were rare compared with courses incorporated with other elements. Most parents would remind their children to study online at home. At first, the biggest challenge of learning online was the lagging platform. Nevertheless, as time went by, the major challenge became the learning motivation. Most students thought it necessary to re-teach face-to-face after online education, while most teachers did not think so. Conclusion Generally speaking, online medical education was satisfying for both students and teachers, although online courses’ diversity with different forms and elements could be enhanced. Infrastructure construction should be considered first for the schools intended to promote online medical education. If the infrastructure were ready, learning motivation would become the biggest challenge for online medical education. Online medical education efficacy evaluation tools need to be developed in the future to narrow the discrepancy of the evaluation between teachers and students.

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Online Medical Education in India – Different Challenges and Probable Solutions in the Age of COVID-19

Cited by 130 publications

References 23 publications

A Validation of Supervised Deep Learning for Gait Analysis in the Cat

A Validation of Supervised Deep Learning for Gait Analysis in the Cat

Application of Tarkhineh Fermented Product to Produce Potato Chips With Strong Probiotic Properties, High Shelf-Life, and Desirable Sensory Characteristics

Students’ and Teachers’ Perspective on the Implementation of Online Medical Education in China: A Qualitative Study

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