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Lessons Learned from the COVID-19 Pandemic: Emphasizing the Emerging Role and Perspectives from Artificial Intelligence, Mobile Health, and Digital Laboratory Medicine.

Authors :
Dabla PK
Gruson D
Gouget B
Bernardini S
Homsak E
Source :
EJIFCC [EJIFCC] 2021 Jun 29; Vol. 32 (2), pp. 224-243. Date of Electronic Publication: 2021 Jun 29 (Print Publication: 2021).
Publication Year :
2021

Abstract

SARS-CoV-2, the new coronavirus causing COVID-19, is one of the most contagious disease of past decades. COVID-19 is different only in that everyone is encountering it for the first time during this pandemic. The world has gone from complete ignorance to a blitz of details in a matter of months. The foremost challenge that the scientific community faces is to understand the growth and transmission capability of the virus. As the world grapples with the global pandemic, people are spending more time than ever before living and working in the digital milieu, and the adoption of Artificial Intelligence (AI) is propelled to an unprecedented level especially as AI has already proven to play an important role in counteracting COVID-19. AI and Data Science are rapidly becoming important tools in clinical research, precision medicine, biomedical discovery and medical diagnostics. Machine learning (ML) and their subsets, such as deep learning, are also referred to as cognitive computing due to their foundational basis and relationship to cognition. To date, AI based techniques are helping epidemiologists in projecting the spread of virus, contact tracing, early detection, monitoring, social distancing, compiling data and training of healthcare workers. Beside AI, the use of telemedicine, mobile health or mHealth and the Internet of Things (IOT) is also emerging. These techniques have proven to be powerful tools in fighting against the pandemic because they provide strong support in pandemic prevention and control. The present study highlights applications and evaluations of these technologies, practices, and health delivery services as well as regulatory and ethical challenges regarding AI/ML-based medical products.<br /> (Copyright © 2021 International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All rights reserved.)

Details

Language :
English
ISSN :
1650-3414
Volume :
32
Issue :
2
Database :
MEDLINE
Journal :
EJIFCC
Publication Type :
Academic Journal
Accession number :
34421492