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Artificial intelligence innovation in healthcare: Relevance of reporting guidelines for clinical translation from bench to bedside.

Authors :
Teo ZL
Kwee A
Lim JC
Lam CS
Ho D
Maurer-Stroh S
Su Y
Chesterman S
Chen T
Tan CC
Wong TY
Ngiam KY
Tan CH
Soon D
Choong ML
Chua R
Wong S
Lim C
Cheong WY
Ting DS
Source :
Annals of the Academy of Medicine, Singapore [Ann Acad Med Singap] 2023 Apr 27; Vol. 52 (4), pp. 199-212. Date of Electronic Publication: 2023 Apr 27.
Publication Year :
2023

Abstract

Artificial intelligence (AI) and digital innovation are transforming healthcare. Technologies such as machine learning in image analysis, natural language processing in medical chatbots and electronic medical record extraction have the potential to improve screening, diagnostics and prognostication, leading to precision medicine and preventive health. However, it is crucial to ensure that AI research is conducted with scientific rigour to facilitate clinical implementation. Therefore, reporting guidelines have been developed to standardise and streamline the development and validation of AI technologies in health. This commentary proposes a structured approach to utilise these reporting guidelines for the translation of promising AI techniques from research and development into clinical translation, and eventual widespread implementation from bench to bedside.<br />Competing Interests: Dr Daniel SW Ting holds a patent on a deep learning system for detection of retinal diseases, co-founded and holds equity of EyRIS Singapore. Dr Carolyn SP Lam holds a patent on a deep learning system for detection of cardiac disease, co-founded and holds equity in Us2.ai. Dr Dean Ho is scientific co-founder and shareholder of KYAN Therapeutics. He is also a co-inventor of pending patents pertaining to AI-based drug development and personalised medicine.

Details

Language :
English
ISSN :
2972-4066
Volume :
52
Issue :
4
Database :
MEDLINE
Journal :
Annals of the Academy of Medicine, Singapore
Publication Type :
Academic Journal
Accession number :
38904533
Full Text :
https://doi.org/10.47102/annals-acadmedsg.2022452