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Artificial intelligence innovation in healthcare: Relevance of reporting guidelines for clinical translation from bench to bedside.
Teo, Zhen Ling; Kwee, Ann; Lim, John Cw; Lam, Carolyn Sp; Ho, Dean; Maurer-Stroh, Sebastian; Su, Yi; Chesterman, Simon; Chen, Tsuhan; Tan, Chorh Chuan; Wong, Tien Yin; Ngiam, Kee Yuan; Tan, Cher Heng; Soon, Danny; Choong, May Ling; Chua, Raymond; Wong, Sutowo; Lim, Colin; Cheong, Wei Yang; Ting, Daniel Sw.
Affiliation
  • Teo ZL; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Kwee A; Department of Endocrinology, Singapore General Hospital, Singapore.
  • Lim JC; Centre of Regulatory Excellence, Duke-NUS Medical School, National University of Singapore, Singapore.
  • Lam CS; Department of Cardiology, National Heart Centre Singapore, Singapore.
  • Ho D; Duke-NUS Medical School, National University of Singapore, Singapore.
  • Maurer-Stroh S; Department of Biomedical Engineering, Institute of Digital Medicine, N.1 Institute of Health and Department of Pharmacology, National University of Singapore, Singapore.
  • Su Y; Bioinformatics Institute and Infectious Diseases Labs, Agency for Science, Technology and Research, Singapore.
  • Chesterman S; Yong Loo Lin School of Medicine and Department of Biological Sciences, National University of Singapore, Singapore.
  • Chen T; Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore.
  • Tan CC; Faculty of Law, National University of Singapore, Singapore.
  • Wong TY; AI Singapore, Singapore.
  • Ngiam KY; AI Singapore, Singapore.
  • Tan CH; School of Computing, National University of Singapore, Singapore.
  • Soon D; Chief Health Scientist Office, Ministry of Health, Singapore.
  • Choong ML; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Chua R; Tsinghua Medicine, Tsinghua University, Beijing, China.
  • Wong S; Group Technology Office, National University Health System, Singapore.
  • Lim C; Centre for Health Innovation, National Healthcare Group, Singapore.
  • Cheong WY; Consortium for Clinical Research and Innovation, Singapore, Singapore.
  • Ting DS; Health Sciences Authority, Singapore.
Ann Acad Med Singap ; 52(4): 199-212, 2023 Apr 27.
Article in En | MEDLINE | ID: mdl-38904533
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Translational Research, Biomedical Limits: Humans Language: En Journal: Ann Acad Med Singap / Ann. Acad. Med. Singap. (Online) / Annals, Academy of Medicine, Singapore (Online) Year: 2023 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Translational Research, Biomedical Limits: Humans Language: En Journal: Ann Acad Med Singap / Ann. Acad. Med. Singap. (Online) / Annals, Academy of Medicine, Singapore (Online) Year: 2023 Document type: Article Affiliation country: Country of publication: