Article Text

Download PDFPDF
Artificial intelligence in gastroenterology and hepatology: how to advance clinical practice while ensuring health equity
  1. Eugenia Uche-Anya1,
  2. Adjoa Anyane-Yeboa1,
  3. Tyler M Berzin2,
  4. Marzyeh Ghassemi3,
  5. Folasade P May4
  1. 1Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
  2. 2Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
  3. 3Institute for Medical and Evaluative Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  4. 4Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA Kaiser Permanente Center for Health Equity and Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, USA
  1. Correspondence to Dr Folasade P May, Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA Kaiser Permanente Center for Health Equity and Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA 90095-6900, USA; fmay{at}mednet.ucla.edu

Abstract

Artificial intelligence (AI) and machine learning (ML) systems are increasingly used in medicine to improve clinical decision-making and healthcare delivery. In gastroenterology and hepatology, studies have explored a myriad of opportunities for AI/ML applications which are already making the transition to bedside. Despite these advances, there is a risk that biases and health inequities can be introduced or exacerbated by these technologies. If unrecognised, these technologies could generate or worsen systematic racial, ethnic and sex disparities when deployed on a large scale. There are several mechanisms through which AI/ML could contribute to health inequities in gastroenterology and hepatology, including diagnosis of oesophageal cancer, management of inflammatory bowel disease (IBD), liver transplantation, colorectal cancer screening and many others. This review adapts a framework for ethical AI/ML development and application to gastroenterology and hepatology such that clinical practice is advanced while minimising bias and optimising health equity.

  • IBD
  • oesophageal cancer
  • liver transplantation
  • colorectal cancer

Statistics from Altmetric.com

Footnotes

  • EU-A and AA-Y are joint first authors.

  • Twitter @tberzin

  • Contributors EU-A and AA-Y are joint first authors and contributed equally to this paper. TMB and FPM supervised this project and conceived the original idea. MG critically reviewed the project and provided AI/ML expertise. EU-A, AA-Y, MG, TMB and FPM have approved this version of the manuscript for publication.

  • Funding FPM is supported by the UCLA Jonsson Comprehensive Cancer Center and the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research Ablon Scholars Program. AA-Y is supported by the National Cancer Institute (award number P50 CA244433) and the Trefler Foundation via MGH Cancer Center.

  • Competing interests TMB is a consultant for Wision AI, Docbot AI, Medtronic and Magentiq Eye. FPM is a consultant for Medtronic and receives research funding from Exact Sciences. AA-Y receives research funding from Pfizer and Exact Sciences, and consulting fees from Janssen Pharmaceuticals.

  • Provenance and peer review Not commissioned; externally peer reviewed.

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.