Syed Ubaid .

Mr. Syed Ubaid .

Jamia Hamdard, New Delhi, Delhi, International
orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 November 2023 in Frontiers in Artificial Intelligence
Verified
Journal Article
Open access
FFFaiza Farhat
Faiza Farhat
SSshahab saquib sohail
shahab saquib sohail
MAMohammed Talha Alam
Mohammed Talha Alam
S.Syed Ubaid .
Syed Ubaid .
SHShakil
Shakil
Dag Øivind MadsenDag Øivind Madsen
Dag Øivind Madsen
COVID-19 has brought significant changes to our political, social, and technological landscape. This paper explores the emergence and global spread of the disease and focuses on the role of Artificial Intelligence (AI) in containing its transmission. To the best of our knowledge, there has been no scientific presentation of the early pictorial representation of the disease's spread. Additionally, we outline various domains where AI has made a significant impact during the pandemic. Our methodology involves searching relevant articles on COVID-19 and AI in leading databases such as PubMed and Scopus to identify the ways AI has addressed pandemic-related challenges and its potential for further assistance. While research suggests that AI has not fully realized its potential against COVID-19, likely due to data quality and diversity limitations, we review and identify key areas where AI has been crucial in preparing the fight against any sudden outbreak of the pandemic. We also propose ways to maximize the utilization of AI's capabilities in this regard.

8 November 2022 in Mathematics
Verified
Journal Article
Open access
PDF file
MAMohammed Talha Alam
Mohammed Talha Alam
SSshahab saquib sohail
shahab saquib sohail
S.Syed Ubaid .
Syed Ubaid .
S.Shakil ..
Shakil ..
ZAZafar Ali
Zafar Ali
Khan MuhammadKhan Muhammad
Khan Muhammad
The deadly threat caused by the rapid spread of COVID-19 has been restricted by virtue of vaccines. However, there is misinformation regarding the certainty and positives outcome of getting vaccinated; hence, many people are reluctant to opt for it. Therefore, in this paper, we identified public sentiments and hesitancy toward the COVID-19 vaccines based on Instagram posts as part of intelligent surveillance. We first retrieved more than 10k publicly available comments and captions posted under different vaccine hashtags (namely, covaxin, covishield, and sputnik). Next, we translated the extracted comments into a common language (English), followed by the calculation of the polarity score of each comment, which helped identify the vaccine sentiments and opinions in the comments (positive, negative, and neutral) with an accuracy of more than 80%. Moreover, upon analysing the sentiments, we found that covaxin received 71.4% positive, 18.5% neutral, and 10.1% negative comments; covishield obtained 64.2% positive, 24.5% neutral, and 11.3% negative post; and sputnik received 55.8% positive, 15.5% neutral, and 28.7% negative sentiments. Understanding vaccination perceptions and views through Instagram comments, captions, and posts is helpful for public health officials seeking to enhance vaccine uptake by promoting positive marketing and reducing negative marketing. In addition to this, some interesting future directions are also suggested considering the investigated problem.