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AI and Machine Learning in IBD: Promising Applications and Remaining Challenges
References
  1. Lewis JD, Parlett LE, Jonsson Funk ML, et al. Incidence, prevalence, and racial and ethnic distribution of inflammatory bowel disease in the United States. Gastroenterology. 2023;165(5):1197-1205.e2. doi:10.1053/j.gastro.2023.07.003
  2. Sharma P. AI shows promise in diagnosis, treatment of IBD, but limitations, concerns remain. Healio. Published June 19, 2023. Accessed January 5, 2024. https://www.healio.com/news/gastroenterology/20230606/ai-shows-promise-in-diagnosis-treatment-of-ibd-but-limitations-concerns-remain
  3. Artificial intelligence (AI) vs. machine learning. Columbia Engineering.Accessed January 5, 2024. https://ai.engineering.columbia.edu/ai-vs-machine-learning/
  4. Zhang B, Shi H, Wang H. Machine learning and AI in cancer prognosis, prediction, and treatment selection: a critical approach. J Multidiscip Healthc. 2023;16:1779-1791. doi:10.2147/JMDH.S410301
  5. 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(2):279-285. doi:10.1111/jgh.15405
  6. Uche-Anya E, Anyane-Yeboa A, Berzin TM, Ghassemi M, May FP. Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity. Gut. 2022;71(9):1909-1915. doi:10.1136/gutjnl-2021-326271
  7. Stafford IS, Gosink MM, Mossotto E, Ennis S, Hauben M. A systematic review of artificial intelligence and machine learning applications to inflammatory bowel disease, with practical guidelines for interpretation. Inflamm Bowel Dis. 2022;28(10):1573-1583. doi:10.1093/ibd/izac115
  8. Gubatan J, Levitte S, Patel A, Balabanis T, Wei MT, Sinha SR. Artificial intelligence applications in inflammatory bowel disease: emerging technologies and future directions. World J Gastroenterol. 2021;27(17):1920-1935. doi:10.3748/wjg.v27.i17.1920
Author and Disclosure Information

Shirley Cohen-Mekelburg, MD, MS
Assistant Professor
Division of Gastroenterology
Michigan Medicine
Director of IBD
VA Ann Arbor Health Care System
Ann Arbor, Michigan

Dr. Cohen-Mekelburg has disclosed no relevant financial relationships.

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Author and Disclosure Information

Shirley Cohen-Mekelburg, MD, MS
Assistant Professor
Division of Gastroenterology
Michigan Medicine
Director of IBD
VA Ann Arbor Health Care System
Ann Arbor, Michigan

Dr. Cohen-Mekelburg has disclosed no relevant financial relationships.

Author and Disclosure Information

Shirley Cohen-Mekelburg, MD, MS
Assistant Professor
Division of Gastroenterology
Michigan Medicine
Director of IBD
VA Ann Arbor Health Care System
Ann Arbor, Michigan

Dr. Cohen-Mekelburg has disclosed no relevant financial relationships.

References
  1. Lewis JD, Parlett LE, Jonsson Funk ML, et al. Incidence, prevalence, and racial and ethnic distribution of inflammatory bowel disease in the United States. Gastroenterology. 2023;165(5):1197-1205.e2. doi:10.1053/j.gastro.2023.07.003
  2. Sharma P. AI shows promise in diagnosis, treatment of IBD, but limitations, concerns remain. Healio. Published June 19, 2023. Accessed January 5, 2024. https://www.healio.com/news/gastroenterology/20230606/ai-shows-promise-in-diagnosis-treatment-of-ibd-but-limitations-concerns-remain
  3. Artificial intelligence (AI) vs. machine learning. Columbia Engineering.Accessed January 5, 2024. https://ai.engineering.columbia.edu/ai-vs-machine-learning/
  4. Zhang B, Shi H, Wang H. Machine learning and AI in cancer prognosis, prediction, and treatment selection: a critical approach. J Multidiscip Healthc. 2023;16:1779-1791. doi:10.2147/JMDH.S410301
  5. 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(2):279-285. doi:10.1111/jgh.15405
  6. Uche-Anya E, Anyane-Yeboa A, Berzin TM, Ghassemi M, May FP. Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity. Gut. 2022;71(9):1909-1915. doi:10.1136/gutjnl-2021-326271
  7. Stafford IS, Gosink MM, Mossotto E, Ennis S, Hauben M. A systematic review of artificial intelligence and machine learning applications to inflammatory bowel disease, with practical guidelines for interpretation. Inflamm Bowel Dis. 2022;28(10):1573-1583. doi:10.1093/ibd/izac115
  8. Gubatan J, Levitte S, Patel A, Balabanis T, Wei MT, Sinha SR. Artificial intelligence applications in inflammatory bowel disease: emerging technologies and future directions. World J Gastroenterol. 2021;27(17):1920-1935. doi:10.3748/wjg.v27.i17.1920
References
  1. Lewis JD, Parlett LE, Jonsson Funk ML, et al. Incidence, prevalence, and racial and ethnic distribution of inflammatory bowel disease in the United States. Gastroenterology. 2023;165(5):1197-1205.e2. doi:10.1053/j.gastro.2023.07.003
  2. Sharma P. AI shows promise in diagnosis, treatment of IBD, but limitations, concerns remain. Healio. Published June 19, 2023. Accessed January 5, 2024. https://www.healio.com/news/gastroenterology/20230606/ai-shows-promise-in-diagnosis-treatment-of-ibd-but-limitations-concerns-remain
  3. Artificial intelligence (AI) vs. machine learning. Columbia Engineering.Accessed January 5, 2024. https://ai.engineering.columbia.edu/ai-vs-machine-learning/
  4. Zhang B, Shi H, Wang H. Machine learning and AI in cancer prognosis, prediction, and treatment selection: a critical approach. J Multidiscip Healthc. 2023;16:1779-1791. doi:10.2147/JMDH.S410301
  5. 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(2):279-285. doi:10.1111/jgh.15405
  6. Uche-Anya E, Anyane-Yeboa A, Berzin TM, Ghassemi M, May FP. Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity. Gut. 2022;71(9):1909-1915. doi:10.1136/gutjnl-2021-326271
  7. Stafford IS, Gosink MM, Mossotto E, Ennis S, Hauben M. A systematic review of artificial intelligence and machine learning applications to inflammatory bowel disease, with practical guidelines for interpretation. Inflamm Bowel Dis. 2022;28(10):1573-1583. doi:10.1093/ibd/izac115
  8. Gubatan J, Levitte S, Patel A, Balabanis T, Wei MT, Sinha SR. Artificial intelligence applications in inflammatory bowel disease: emerging technologies and future directions. World J Gastroenterol. 2021;27(17):1920-1935. doi:10.3748/wjg.v27.i17.1920
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Nearly 1 in 100 Americans have Inflammatory Bowel Disease (IBD), with up to 56,000 new cases being diagnosed each year.IBD is a complex disease with a myriad of presentations, possible treatment approaches, and patient outcomes. Artificial intelligence (AI)—a field of technology which began in the 1950s—refers to the ability of computers to learn and perform tasks that would have typically required human intelligence, while “machine learning” refers to the development of the algorithms that help AI learn patterns from data.2,3 The goal in many industries, including health care, is for AI to aid in and improve decision-making. Applications of AI including machine learning already greatly influence the oncology space, aiding in risk assessment, early diagnosis, prognosis, and treatment decision-making.4 Similar utilizations are being investigated to help improve the quality and efficiency of care for patients with IBD, but there is still much research to be done before we can fully leverage such tools in everyday practice.5

Although extensive progress in AI has been made since the turn of the century, several limitations remain. Poor-quality data sets may lead to inaccurate predictions, and it is difficult to generalize data sets to minority populations. In health care, clinicians must also understand and be able to interpret the algorithms in order to trust and apply them in practice. Lastly, and importantly, there are ethical concerns regarding patient privacy in data collection.6

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