Artificial intelligence for gastroenterology: Singapore artificial intelligence for Gastroenterology Working Group Position Statement.
Artificial intelligence
Gastroenterology
Public policy
Journal
Journal of gastroenterology and hepatology
ISSN: 1440-1746
Titre abrégé: J Gastroenterol Hepatol
Pays: Australia
ID NLM: 8607909
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
revised:
10
05
2023
received:
12
03
2023
accepted:
11
05
2023
medline:
23
10
2023
pubmed:
6
6
2023
entrez:
5
6
2023
Statut:
ppublish
Résumé
Successful implementation of artificial intelligence in gastroenterology and hepatology practice requires more than technology. There are ethical, legal, and social issues that need to be settled. A group consisting of AI developers (engineer), AI users (gastroenterologist, hepatologist, and surgeon) and AI regulators (ethicist and administrator) formed a Working Group to draft these Positions Statements with the objective of arousing public and professional interest and dialogue, to promote ethical considerations when implementing AI technology, to suggest to policy makers and health authorities relevant factors to take into account when approving and regulating the use of AI tools, and to engage the profession in preparing for change in clinical practice. These series of Position Statements point out the salient issues to maintain the trust between care provider and care receivers, and to legitimize the use of a non-human tool in healthcare delivery. It is based on fundamental principles such as respect, autonomy, privacy, responsibility, and justice. Enforcing the use of AI without considering these factor risk damaging the doctor-patient relationship.
Sections du résumé
BACKGROUND
BACKGROUND
Successful implementation of artificial intelligence in gastroenterology and hepatology practice requires more than technology. There are ethical, legal, and social issues that need to be settled.
AIM
OBJECTIVE
A group consisting of AI developers (engineer), AI users (gastroenterologist, hepatologist, and surgeon) and AI regulators (ethicist and administrator) formed a Working Group to draft these Positions Statements with the objective of arousing public and professional interest and dialogue, to promote ethical considerations when implementing AI technology, to suggest to policy makers and health authorities relevant factors to take into account when approving and regulating the use of AI tools, and to engage the profession in preparing for change in clinical practice.
STATEMENTS
UNASSIGNED
These series of Position Statements point out the salient issues to maintain the trust between care provider and care receivers, and to legitimize the use of a non-human tool in healthcare delivery. It is based on fundamental principles such as respect, autonomy, privacy, responsibility, and justice. Enforcing the use of AI without considering these factor risk damaging the doctor-patient relationship.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1669-1676Informations de copyright
© 2023 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.
Références
Cohen-Mekelburg S, Berry S, Stidham RW, Zhu J, Waljee AK. Clinical applications of artificial intelligence and machine learning-based methods in inflammatory bowel disease. J Gastroenterol Hepatol 2021; 36: 279-285.
Shung DL, Au B, Taylor RA et al. Validation of a Machine Learning Model That Outperforms Clinical Risk Scoring Systems for Upper Gastrointestinal Bleeding. Gastroenterology 2020; 158: 160-167.
Mori Y, Kudo S-e, Misawa M et al. Real-time use of artificial intelligence in identification of diminutive polyps during colonoscopy: a prospective study. Ann Intern Med 2018; 169: 357.
Wong GLH, Yuen PC, Ma AJ, Chan AWH, Leung HHW, Wong VWS. Artificial intelligence in prediction of non-alcoholic fatty liver disease and fibrosis. J Gastroenterol Hepatol 2021; 36: 543-550.
Shung DL, Sung JJY. Challenges of developing artificial intelligence-assisted tools for clinical medicine. J Gastroenterol Hepatol 2021; 36: 295-298.
World Health Organization. Ethics and governance of artificial intelligence for health: WHO guidance. 2021/06/28/2021. https://www.who.int/publications/i/item/9789240029200
Singapore Computer Society, Infocomm Media Development Authority. Artificial intelligence ethics & governance body of knowledge. https://www.scs.org.sg/bok/ai-ethics
Stewart C, Wong SKY, Sung JJY. Mapping ethico-legal principles for the use of artificial intelligence in gastroenterology. J Gastroenterol Hepatol 2021; 36: 1143-1148.
OECD AI Policy Observatory. OECD AI Principles overview. 2019 2019. https://oecd.ai/en/ai-principles
European Commission. Ethics guidelines for trustworthy AI. 2019. https://data.europa.eu/doi/10.2759/346720
The International Conference of Data Protection Privacy Commissioners. Resolutions and Declaration from the 2018 International Conference of Data Protection and Privacy Commissioners - Declaration on Ethics and Data Protection in Artificial Intelligence. 2018. https://edps.europa.eu/sites/default/files/publication/icdppc-40th_ai-declaration_adopted_en_0.pdf
Gong D, Wu L, Zhang J et al. Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study. Lancet Gastroenterol Hepatol 2020; 5: 352-361.
Hassan C, Balsamo G, Lorenzetti R, Zullo A, Antonelli G. Artificial intelligence allows leaving-in-situ colorectal polyps. Clin Gastroenterol Hepatol 2022; 20: 2505-13 e4.
Mori Y, Kudo S-e, Misawa M et al. Artificial intelligence-assisted colonic endocytoscopy for cancer recognition: a multicenter study. Endosc Int Open 2021; 09: E1004-E1011.
Rondonotti E, Hassan C, Tamanini G et al. Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: the Artificial intelligence BLI Characterization (ABC) study. Endoscopy 2023; 55: 14-22.
Isakov O, Dotan I, Ben-Shachar S. Machine learning-based gene prioritization identifies novel candidate risk genes for inflammatory bowel disease. Inflamm Bowel Dis 2017; 23: 1516-1523.
Takenaka K, Ohtsuka K, Fujii T et al. Development and validation of a deep neural network for accurate evaluation of endoscopic images from patients with ulcerative colitis. Gastroenterology 2020; 158: 2150-2157.
Waljee AK, Joyce JC, Wang S et al. Algorithms outperform metabolite tests in predicting response of patients with inflammatory bowel disease to thiopurines. Clin Gastroenterol Hepatol 2010; 8: 143-150.
Fialoke S, Malarstig A, Miller MR, Dumitriu A. Application of machine learning methods to predict non-alcoholic steatohepatitis (NASH) in non-alcoholic fatty liver (NAFL) patients. AMIA Annu Symp Proc 2018; 2018: 430-439.
Schawkat K, Ciritsis A, Von Ulmenstein S et al. Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology. Eur Radiol 2020; 30: 4675-4685.
Wang F, Kaushal R, Khullar D. Should health care demand interpretable artificial intelligence or accept “black box” medicine? Ann Intern Med 2020; 172: 59.
Poon AIF, Sung JJY. Opening the black box of AI-medicine. J Gastroenterol Hepatol 2021; 36: 581-584.
Khullar D, Casalino LP, Qian Y, Lu Y, Krumholz HM, Aneja S. Perspectives of patients about artificial intelligence in health care. JAMA Netw Open 2022; 5: e2210309.
Xafis V, Schaefer GO, Labude MK et al. An ethics framework for big data in health and research. ABR 2019; 11: 227-254.
Reddy S, Allan S, Coghlan S, Cooper P. A governance model for the application of AI in health care. J Am Med Inform Assoc 2020; 27: 491-497.
Li JW, Chia T, Fock KM, Chong KDW, Wong YJ, Ang TL. Artificial intelligence and polyp detection in colonoscopy: use of a single neural network to achieve rapid polyp localization for clinical use. J Gastroenterol Hepatol 2021; 36: 3298-3307.
Lam TYT, Cheung MFK, Munro YL, Lim KM, Shung D, Sung JJY. Randomized controlled trials of artificial intelligence in clinical practice: systematic review. J Med Internet Res 2022; 24: e37188.
Xu H, Tang RSY, Lam TYT et al. Artificial intelligence-assisted colonoscopy for colorectal cancer screening: a multicenter randomized controlled trial. Clin Gastroenterol Hepatol 2023; 21: 337-46 e3.
U. S. Food Drug Administration. Software as a Medical Device (SaMD). 2018/04/12/2018. https://www.fda.gov/medical-devices/digital-health-center-excellence/software-medical-device-samd
Ministry of Health Singapore. Artificial intelligence in healthcare. https://www.moh.gov.sg/licensing-and-regulation/artificial-intelligence-in-healthcare
Webster G, Creemers R, Kania E, Triolo P. Full Translation: China's ‘New Generation Artificial Intelligence Development Plan’ (2017). Stanford Cyber Policy Center; 2017.
European Union. The general data protection regulation. 2018/05/25/2018. https://www.consilium.europa.eu/en/policies/data-protection/data-protection-regulation/#:~:text=data%20protection%20rules-,What%20is%20the%20GDPR%3F,application%20on%2025%20May%202018
Personal Data Protection Act 2012. https://sso.agc.gov.sg/Act/PDPA2012
Messmann H, Bisschops R, Antonelli G et al. Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy 2022; 54: 1211-1231.
He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K. The practical implementation of artificial intelligence technologies in medicine. Nat Med 2019; 25: 30-36.
Sung JJ, Poon NC. Artificial intelligence in gastroenterology: where are we heading? Front Med 2020; 14: 511-517.