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AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data.

Authors :
Santosh, K. C.
Source :
Journal of Medical Systems. May2020, Vol. 44 Issue 5, p1-5. 5p. 2 Black and White Photographs, 1 Diagram, 2 Maps.
Publication Year :
2020

Abstract

The novel coronavirus (COVID-19) outbreak, which was identified in late 2019, requires special attention because of its future epidemics and possible global threats. Beside clinical procedures and treatments, since Artificial Intelligence (AI) promises a new paradigm for healthcare, several different AI tools that are built upon Machine Learning (ML) algorithms are employed for analyzing data and decision-making processes. This means that AI-driven tools help identify COVID-19 outbreaks as well as forecast their nature of spread across the globe. However, unlike other healthcare issues, for COVID-19, to detect COVID-19, AI-driven tools are expected to have active learning-based cross-population train/test models that employs multitudinal and multimodal data, which is the primary purpose of the paper. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01485598
Volume :
44
Issue :
5
Database :
Academic Search Index
Journal :
Journal of Medical Systems
Publication Type :
Academic Journal
Accession number :
143018941
Full Text :
https://doi.org/10.1007/s10916-020-01562-1