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Articles 31 - 35 of 35
Full-Text Articles in Medicine and Health Sciences
Nutritional Approach For Increasing Public Health During Pandemic Of Covid-19: A Comprehensive Review Of Antiviral Nutrients And Nutraceuticals, Vahideh Ebrahimzadeh-Attari, Ghodratollah Panahi, James R. Hébert Scd, Alireza Ostadrahimi, Maryam Saghafi-Asl, Neda Lotfi-Yaghin, Behzad Baradaran
Nutritional Approach For Increasing Public Health During Pandemic Of Covid-19: A Comprehensive Review Of Antiviral Nutrients And Nutraceuticals, Vahideh Ebrahimzadeh-Attari, Ghodratollah Panahi, James R. Hébert Scd, Alireza Ostadrahimi, Maryam Saghafi-Asl, Neda Lotfi-Yaghin, Behzad Baradaran
Faculty Publications
Background: The novel coronavirus (COVID-19) is considered as the most life-threatening pandemic disease during the last decade. The individual nutritional status, though usually ignored in the management of COVID-19, plays a critical role in the immune function and pathogenesis of infection. Accordingly, the present review article aimed to report the effects of nutrients and nutraceuticals on respiratory viral infections including COVID-19, with a focus on their mechanisms of action.
Methods: Studies were identified via systematic searches of the databases including PubMed/ MEDLINE, ScienceDirect, Scopus, and Google Scholar from 2000 until April 2020, using keywords. All relevant clinical and experimental studies …
A Novel Augmented Deep Transfer Learning For Classification Of Covid-19 And Other Thoracic Diseases From X-Rays, Fouzia Atlaf, Syed M. S. Islam, Naeem K. Janjua
A Novel Augmented Deep Transfer Learning For Classification Of Covid-19 And Other Thoracic Diseases From X-Rays, Fouzia Atlaf, Syed M. S. Islam, Naeem K. Janjua
Research outputs 2014 to 2021
Deep learning has provided numerous breakthroughs in natural imaging tasks. However, its successful application to medical images is severely handicapped with the limited amount of annotated training data. Transfer learning is commonly adopted for the medical imaging tasks. However, a large covariant shift between the source domain of natural images and target domain of medical images results in poor transfer learning. Moreover, scarcity of annotated data for the medical imaging tasks causes further problems for effective transfer learning. To address these problems, we develop an augmented ensemble transfer learning technique that leads to significant performance gain over the conventional transfer …
Sentiment Analysis Of Long-Term Social Data During The Covid-19 Pandemic, Sophanna Ek, Marco Curci, Xiaokun Yang, Beiyu Lin, Pinchao Liu, Hailu Xu
Sentiment Analysis Of Long-Term Social Data During The Covid-19 Pandemic, Sophanna Ek, Marco Curci, Xiaokun Yang, Beiyu Lin, Pinchao Liu, Hailu Xu
Computer Science Faculty Publications and Presentations
The COVID-19 pandemic has bringing the “infodemic” in the social media worlds. Various social platforms play a significant role in instantly acquiring the latest updates of the pandemic. Social media such as Twitter and Facebook produce vast amounts of posts related to the virus, vaccines, economics, and politics. In order to figure out how public opinion and sentiments are expressed during the pandemic, this work analyzes the long-term social posts from social media and conducts sentiment analysis on tweets within 12 months. Our findings show the trend topics of long-term social communities during the pandemic and express people’s attitudes towards …
Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam
Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam
Research Collection School Of Computing and Information Systems
The COVID-19 pandemic triggered a large-scale work-from-home trend globally in recent months. In this paper, we study the phenomenon of “work-from-home” (WFH) by performing social listening. We propose an analytics pipeline designed to crawl social media data and perform text mining analyzes on textual data from tweets scrapped based on hashtags related to WFH in COVID-19 situation. We apply text mining and NLP techniques to analyze the tweets for extracting the WFH themes and sentiments (positive and negative). Our Twitter theme analysis adds further value by summarizing the common key topics, allowing employers to gain more insights on areas of …
Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman
Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman
Research Collection School Of Computing and Information Systems
Just like most universities around the world, the senior management at Singapore Management University decided to move all courses to a virtual, online, synchronous mode, giving instructors a very short notice period—one week—to make this transition. In this paper, we describe the challenges, practical solutions adopted, and the lessons learnt in rapidly transitioning a face-to-face Master’s degree course in Text Analytics and Applications into a virtual, online, course format that could deliver a quality learning experience.