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Journal of Medical Systems

Erschienen in:

18.03.2020 | COVID-19 | Education & Training

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

verfasst von: K. C. Santosh

Erschienen in: Journal of Medical Systems | Ausgabe 5/2020

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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.

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Titel: AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data
verfasst von: K. C. Santosh
Publikationsdatum: 18.03.2020
Verlag: Springer US
Schlagwort: COVID-19
Erschienen in: Journal of Medical Systems / Ausgabe 5/2020
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-020-01562-1

Springer Medizin

Abstract

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