AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data.
J Med Syst
; 44(5): 93, 2020 Mar 18.
Article
in English
| MEDLINE | ID: covidwho-10003
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Algorithms
/
Artificial Intelligence
/
Disease Outbreaks
/
Coronavirus Infections
/
Machine Learning
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Topics:
Long Covid
Limits:
Humans
Language:
English
Journal:
J Med Syst
Year:
2020
Document Type:
Article
Affiliation country:
S10916-020-01562-1
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