Digital Education for the Deployment of Artificial Intelligence in Health Care
Name
Malerbi et al.pdf
Size
70.65 KB
Format
Adobe PDF
Checksum (MD5)
7fd0bcf88a1d3c9dddb8ec2e6238c0d7
Author(s)
Malerbi, Fernando Korn
Nakayama, Luis Filipe
Gayle Dychiao, Robyn
Zago Ribeiro, Lucas
Villanueva, Cleva
Celi, Leo Anthony
Regatieri, Caio Vinicius
Date Issued
June 22, 2023
Publisher
JMIR Publications Inc.
Citation
Malerbi FK, Nakayama LF, Gayle Dychiao R, Zago Ribeiro L, Villanueva C, Celi LA, Regatieri CV
Digital Education for the Deployment of Artificial Intelligence in Health Care
J Med Internet Res 2023;25:e43333.
Version
Final published version
Abstract
Artificial Intelligence (AI) represents a significant milestone in health care's digital transformation. However, traditional health care education and training often lack digital competencies. To promote safe and effective AI implementation, health care professionals must acquire basic knowledge of machine learning and neural networks, critical evaluation of data sets, integration within clinical workflows, bias control, and human-machine interaction in clinical settings. Additionally, they should understand the legal and ethical aspects of digital health care and the impact of AI adoption. Misconceptions and fears about AI systems could jeopardize its real-life implementation. However, there are multiple barriers to promoting electronic health literacy, including time constraints, overburdened curricula, and the shortage of capacitated professionals. To overcome these challenges, partnerships among developers, professional societies, and academia are essential. Integrating specialists from different backgrounds, including data specialists, lawyers, and social scientists, can significantly contribute to combating digital illiteracy and promoting safe AI implementation in health care.
Subjects
Health Informatics
MIT Department
Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.2196/43333
