ABSTRACT
Vision Transformers (ViTs), with the magnificent potential to unravel the information contained within images, have evolved as one of the most contemporary and dominant architectures that are being used in the field of computer vision. These are immensely utilized by plenty of researchers to perform new as well as former experiments. Here, in this article, we investigate the intersection of vision transformers and medical images. We proffered an overview of various ViT based frameworks that are being used by different researchers to decipher the obstacles in medical computer vision. We surveyed the applications of Vision Transformers in different areas of medical computer vision such as image-based disease classification, anatomical structure segmentation, registration, region-based lesion detection, captioning, report generation, and reconstruction using multiple medical imaging modalities that greatly assist in medical diagnosis and hence treatment process. Along with this, we also demystify several imaging modalities used in medical computer vision. Moreover, to get more insight and deeper understanding, the self-attention mechanism of transformers is also explained briefly. Conclusively, the ViT based solutions for each image analytics task are critically analyzed, open challenges are discussed and the pointers to possible solutions for future direction are deliberated. We hope this review article will open future research directions for medical computer vision researchers.
ABSTRACT
In recent times, humans who have been exposed to influenza A viruses (IAV) may not become hostile. Despite the fact that KLRD1 has been discovered as an influenza susceptibility biomarker, it remains to be seen if pre-exposure host gene expression can predict flu symptoms. In this paper, we enable the examination of flu using deep neural networks from input human gene expression datasets with various subtype viruses. This study enables the utilization of these datasets to forecast the spread of flu and can provide the necessary steps to eradicate the flu. The simulation is conducted to test the efficiency of the model in predicting the spread against various input datasets. The results of the simulation show that the proposed method offers a better prediction ability of 2.98% more than other existing methods in finding the spread of flu.
ABSTRACT
Background: COVID-19 pandemic is a global challenge. It's just not limited to physical impact but also has serious mental, social and economic impacts all over the world. Self-harm and suicides are its extreme effects. Aim(s): To study and analyze the patterns of suicide during the COVID-19 pandemic. Material(s) and Method(s): A retrospective autopsy-based analysis of suicidal deaths occurred during March 2020 and February 2021 was conducted in the department of Forensic medicine, Sri Venkateswara Medical College, Tirupati. A total of 897 autopsies were conducted, out of which 248 were suicides. Result(s): 248 cases of suicide were studied among them 182 were male and 66 were female. Majority of the deaths were due to hanging (94, 37.90%) followed by poisoning (61,24.59%). The most important contributing factor for suicide was domestic conflict/ violence (85,34.27%) followed by financial loss or loss of income (81,32.66%). Conclusion(s): This study reemphasizes the need of proactive responses to psychological health especially during events of stressful conditions like lock down and pandemic. Social, economic and public health response is necessary to prevent suicidal behavior. Copyright © 2022, Institute of Medico-legal Publication. All rights reserved.
ABSTRACT
Objective: To determine the viewpoints of the faculty members about digital learning at Rawalpindi Medical University (RMU) during COVID pandemic. Methodology: This cross-sectional descriptive study was carried out during August 2020 among 89 faculty members of RMU with diverse designation. Data were collected by using digitally administered Google forms based on 5 point likert scale through convenience sampling. Information was gathered regarding perceived advantages and key troubles faced in smooth execution of online teaching. Data analysis was done with SPSS version 25.0. Results: Of the total 89 faculty members, 30.4% were demonstrators, 23.6% Senior Registrars and 21.3% Assistant Professors. About 87% faculty agreed with adequate curriculum coverage during online teaching, 84% found MS Teams interface user friendly while 82% conveniently generated link for their online class. About 38% faculty confronted with internet connectivity issues while 40% were satisfied with students’ response during online class. Only 22% respondents agreed with impartiality of online assessments and judgment of competencies. Conclusion: Digital learning greatly facilitated in academic continuity during pandemic. However, provision of broad band internet facility, making sessions interactive and using diverse online assessment modalities can be helpful to much extent in justified appraisal of clinical competencies. © 2022, Pakistan Medical Association. All rights reserved.
ABSTRACT
Malaysia has been relatively successful in managing the COVID-19 pandemic, with the number of deaths and infections lower than neighboring countries and many developed economies. This paper will share Malaysia's experience in fighting the pandemic, particularly the key success factors in managing the health impact during the period of January to August 2020. The speedy preparation and planning by the Health Ministry even before the country registered its first case was instrumental in ensuring that the country was ready to face the pandemic. Lessons learned from previous experience with epidemics such as Nipah, SARS, MERS, and H1N1 were also key to the speedy responses. Effective communication helped to ensure the public's support of measures imposed by the government to reduce the spread of the virus. However, while the country managed the health crisis relatively well, the handling of the economy is rather poor, with the economic impact being much worse than what was experienced during the 1997-98 Asian financial crisis, and the 2008-09 global financial crisis. This paper will end with suggestions of several policy interventions to mitigate the economic impact of COVID-19, particularly for vulnerable groups.