Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force
In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In th...
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| Veröffentlicht in: | Gastrointestinal endoscopy 2023-05, Vol.97 (5), p.815-824.e1 |
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| container_issue | 5 |
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| container_title | Gastrointestinal endoscopy |
| container_volume | 97 |
| creator | Parasa, Sravanthi Repici, Alessandro Berzin, Tyler Leggett, Cadman Gross, Seth A. Sharma, Prateek |
| description | In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In this article, we provide a guiding framework for all stakeholders in the endoscopy AI ecosystem regarding the standards, metrics, and evaluation methods for emerging and existing AI applications to aid in their clinical adoption and implementation. We also provide guidance and best practices for evaluation of AI technologies as they mature in the endoscopy space. Note, this is a living document; periodic updates will be published as progress is made and applications evolve in the field of AI in endoscopy. |
| doi_str_mv | 10.1016/j.gie.2022.10.016 |
| format | Article |
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| identifier | ISSN: 0016-5107 |
| ispartof | Gastrointestinal endoscopy, 2023-05, Vol.97 (5), p.815-824.e1 |
| issn | 0016-5107 1097-6779 |
| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals Complete |
| subjects | Algorithms Artificial Intelligence Benchmarking Ecosystem Endoscopy, Gastrointestinal Humans Reproducibility of Results |
| title | Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force |
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