©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Jun 27, 2024; 16(6): 1517-1520
Published online Jun 27, 2024. doi: 10.4240/wjgs.v16.i6.1517
Published online Jun 27, 2024. doi: 10.4240/wjgs.v16.i6.1517
From the mathematical model to the patient: The scientific and human aspects of artificial intelligence in gastrointestinal surgery
Javier Arredondo Montero, Department of Pediatric Surgery, Complejo Asistencial Universitario de León, Castilla y León, León 24008, Spain
Author contributions: Arredondo Montero J manuscript conception and design; writing, review and editing; literature review.
Conflict-of-interest statement: The author has no conflict of interest.
Corresponding author: Javier Arredondo Montero, MD, PhD, Pediatric Surgeon. Department of Pediatric Surgery, Complejo Asistencial Universitario de León, c/Altos de Nava s/n, Castilla y León, León 24008, Spain. javier.montero.arredondo@gmail.com
Received: March 10, 2024
Revised: April 3, 2024
Accepted: April 22, 2024
Published online: June 27, 2024
Processing time: 111 Days and 11.6 Hours
Revised: April 3, 2024
Accepted: April 22, 2024
Published online: June 27, 2024
Processing time: 111 Days and 11.6 Hours
Core Tip
Core Tip: Recent medical literature shows that the application of artificial intelligence models in gastrointestinal pathology is an exponentially growing field. In this work, the authors present the development of a predictive algorithm for early post-surgical complications in Crohn's disease based on a Random Forest model with exceptional predictive ability for complications within the cohort. The present work, based on logical and reasoned, clinical, and applicable aspects lays, a solid foundation for future prospective work to further develop post-surgical prognostic tools for inflammatory bowel disease.