Cited by 512Artificial Intelligence in Healthcare and EducationArtificial Intelligence ApplicationsArtificial Intelligence in Healthcare

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The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

Aung, Yuri Y M, Wong, David C S, Ting, Daniel S W·2021·British Medical Bulletin

DOI 10.1093/bmb/ldab016

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Abstract

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and future scope. SOURCES OF DATA: A review of the English literature was conducted with search terms 'AI' or 'ML' or 'deep learning' and 'healthcare' or 'medicine' using PubMED and Google Scholar from 2000-2021. AREAS OF AGREEMENT: AI could transform physician workflow and patient care through its applications, from assisting physicians and replacing administrative tasks to augmenting medical knowledge. AREAS OF CONTROVERSY: From challenges training ML systems to unclear accountability, AI's implementation is difficult and incremental at best. Physicians also lack understanding of what AI implementation could represent. GROWING POINTS: AI can ultimately prove beneficial in healthcare, but requires meticulous governance similar to the governance of physician conduct. AREAS TIMELY FOR DEVELOPING RESEARCH: Regulatory guidelines are needed on how to safely implement and assess AI technology, alongside further research into the specific capabilities and limitations of its medical use.

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“The use of AI would relieve the burden on health care professionals and increase the quality of work performed by reducing the possibility of errors and increasing accuracy (Aung et al., 2021).”
Background
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Authors: Aung, Y. Y. M., Wong, D. C. S., & Ting, D. S. W.
Affiliations: Imperial College London (GB)
University of Cambridge (GB)
National University of Singapore (SG)
Corresponding author: Ting, Daniel S W
ORCID: Aung, Yuri Y M
Wong, David C S
Ting, Daniel S W
Venue: British Medical Bulletin
Publisher: Oxford University Press (OUP)
Published: 2021-08-17
Volume: 139
Issue: 1
Pages: 4-15
ISSN: 0007-1420 (ISSN-L)
1471-8391
DOI: 10.1093/bmb/ldab016
OpenAlex: W3196012986
Cited by: 511
References: 46
Citations by year: 2026: 111 · 2025: 161 · 2024: 131 · 2023: 83 · 2022: 22 · 2021: 3
FWCI: 4.86
Type: journal article
Language: en
Open access: closed
Locations: British Medical Bulletin (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords: artificial intelligence in healthcare, machine learning, deep learning, physician workflow, administrative automation, AI implementation challenges, accountability, AI governance, regulatory guidelines, AI safety, AI limitations
MeSH terms: Machine Learning, Artificial Intelligence, Delivery of Health Care, Humans, Medicine

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The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

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