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Harnessing the Power of AI to Enhance Endoscopy: Promises and Pitfalls
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Eugenia Uche-Anya, MD, MPH

Click to view more from Gastroenterology Data Trends 2023. 

References
  1. Jin Z et al. BioMed Eng OnLine. 2022;21(1):12. doi:10.1186/s12938-022-00979-
  2. Buendgens L, Cifci D, Ghaffari Laleh N, et al. Sci Rep. 2022;12(1):4829. doi:10.1038/s41598-022-08773-1
  3. Uche-Anya EN, Berzin TM. Artificial intelligence applications in colonoscopy. GI & Hepatology News. January 24, 2023. https://www.mdedge.com/gihepnews/article/260769/mixed-topics/artificial-intelligence-applications-colonoscopy
  4. Rondonotti E et al. Endoscopy. 2023;55(1):14-22. doi:10.1055/a-1852-0330
  5. Antonelli G et al. Ann Gastroenterol. 2023;36(2):114-122. doi:10.20524/aog.2023.0781
  6. van der Zander QEW et al. Endoscopy. 2021;53(12):1219-1226. doi:10.1055/a-1343-159
  7. Areia PM et al. Lancet Digital Health. 2022;4(6):e436-e444. doi:10.1016/S2589-7500(22)00042-5
  8. Sumiyama K et al. Dig Endosc. 2021;33(2):218-230. doi:10.1111/den.13837
  9. Berzin TM et al. Gastrointest Endosc. 2020;92(4):951-959. doi:10.1016/j.gie.2020.06.035
  10. Mori Y et al. Dig Endosc. 2023;35(4):422-429. doi:10.1111/den.14531
  11. Uche-Anya E et al. Gut. 2022;71(9):1909-1915. doi:10.1136/gutjnl-2021-326271
  12. Moor M et al. Nature. 2023;616(7956):259-265. 10.1038/s41586-023-05881-4
  13. Kather JN et al. NPJ Digit Med. 2022;5(1):90. doi:10.1038/s41746-022-00634-5
Author and Disclosure Information

Fellow
Division of Gastroenterology
Massachusetts General Hospital
Harvard Medical School
Boston, MA

Publications
GI and Hepatology News
Topics
Endoscopy
Author(s)
Eugenia Uche-Anya, MD, MPH
Author(s)
Eugenia Uche-Anya, MD, MPH
Author and Disclosure Information

Fellow
Division of Gastroenterology
Massachusetts General Hospital
Harvard Medical School
Boston, MA

Author and Disclosure Information

Fellow
Division of Gastroenterology
Massachusetts General Hospital
Harvard Medical School
Boston, MA

Click to view more from Gastroenterology Data Trends 2023. 

Click to view more from Gastroenterology Data Trends 2023. 

References
  1. Jin Z et al. BioMed Eng OnLine. 2022;21(1):12. doi:10.1186/s12938-022-00979-
  2. Buendgens L, Cifci D, Ghaffari Laleh N, et al. Sci Rep. 2022;12(1):4829. doi:10.1038/s41598-022-08773-1
  3. Uche-Anya EN, Berzin TM. Artificial intelligence applications in colonoscopy. GI & Hepatology News. January 24, 2023. https://www.mdedge.com/gihepnews/article/260769/mixed-topics/artificial-intelligence-applications-colonoscopy
  4. Rondonotti E et al. Endoscopy. 2023;55(1):14-22. doi:10.1055/a-1852-0330
  5. Antonelli G et al. Ann Gastroenterol. 2023;36(2):114-122. doi:10.20524/aog.2023.0781
  6. van der Zander QEW et al. Endoscopy. 2021;53(12):1219-1226. doi:10.1055/a-1343-159
  7. Areia PM et al. Lancet Digital Health. 2022;4(6):e436-e444. doi:10.1016/S2589-7500(22)00042-5
  8. Sumiyama K et al. Dig Endosc. 2021;33(2):218-230. doi:10.1111/den.13837
  9. Berzin TM et al. Gastrointest Endosc. 2020;92(4):951-959. doi:10.1016/j.gie.2020.06.035
  10. Mori Y et al. Dig Endosc. 2023;35(4):422-429. doi:10.1111/den.14531
  11. Uche-Anya E et al. Gut. 2022;71(9):1909-1915. doi:10.1136/gutjnl-2021-326271
  12. Moor M et al. Nature. 2023;616(7956):259-265. 10.1038/s41586-023-05881-4
  13. Kather JN et al. NPJ Digit Med. 2022;5(1):90. doi:10.1038/s41746-022-00634-5
References
  1. Jin Z et al. BioMed Eng OnLine. 2022;21(1):12. doi:10.1186/s12938-022-00979-
  2. Buendgens L, Cifci D, Ghaffari Laleh N, et al. Sci Rep. 2022;12(1):4829. doi:10.1038/s41598-022-08773-1
  3. Uche-Anya EN, Berzin TM. Artificial intelligence applications in colonoscopy. GI & Hepatology News. January 24, 2023. https://www.mdedge.com/gihepnews/article/260769/mixed-topics/artificial-intelligence-applications-colonoscopy
  4. Rondonotti E et al. Endoscopy. 2023;55(1):14-22. doi:10.1055/a-1852-0330
  5. Antonelli G et al. Ann Gastroenterol. 2023;36(2):114-122. doi:10.20524/aog.2023.0781
  6. van der Zander QEW et al. Endoscopy. 2021;53(12):1219-1226. doi:10.1055/a-1343-159
  7. Areia PM et al. Lancet Digital Health. 2022;4(6):e436-e444. doi:10.1016/S2589-7500(22)00042-5
  8. Sumiyama K et al. Dig Endosc. 2021;33(2):218-230. doi:10.1111/den.13837
  9. Berzin TM et al. Gastrointest Endosc. 2020;92(4):951-959. doi:10.1016/j.gie.2020.06.035
  10. Mori Y et al. Dig Endosc. 2023;35(4):422-429. doi:10.1111/den.14531
  11. Uche-Anya E et al. Gut. 2022;71(9):1909-1915. doi:10.1136/gutjnl-2021-326271
  12. Moor M et al. Nature. 2023;616(7956):259-265. 10.1038/s41586-023-05881-4
  13. Kather JN et al. NPJ Digit Med. 2022;5(1):90. doi:10.1038/s41746-022-00634-5
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Harnessing the Power of AI to Enhance Endoscopy: Promises and Pitfalls
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The availability of AI technologies to improve the overall quality of GI endoscopy has grown significantly over the last decade.1 AI algorithms have shown promise in detecting malignant, infectious, and inflammatory diseases in both upper and lower GI endoscopy imaging.2 Most AI research in endoscopy is currently focused on computer-aided detection (CADe) and diagnosis (CADx), but other computer vision tools are also in development, ranging from algorithms to measure IBD activity to dysplasia detection in Barrett's esophagus.2,3 

Improved lesion detection and classification with AI can support clinical decision-making and lead to better patient outcomes, cost savings, clinician time management, and other efficiencies within the health care system.2-7 However, some substantial barriers must be overcome and current projections must be validated with clinical and real-world trials before we can fully rely on AI in these settings.8-11

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