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
em En
| MEDLINE
| ID: mdl-32189081
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.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Pneumonia Viral
/
Algoritmos
/
Inteligência Artificial
/
Surtos de Doenças
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Infecções por Coronavirus
/
Aprendizado de Máquina
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article