Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease

Our models, based on accessible clinical features, were able to effectively predict EEN success above chance. This supports the plausibility of building clinical tools to assist precision therapy for pCD patients.

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Publication Details

Journal
Journal of Pediatric Gastroenterology and Nutrition
Published
2025-11-29
DOI
https://doi.org/10.1002/jpn3.70299
Primary Topic
Inflammatory Bowel Disease
Type
article
Field-Weighted Citation Impact
0.00
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article

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease

Wael El‐Matary, Roberto Vega, R G Suarez Suarez, Anthony Otley et al.
Journal of Pediatric Gastroenterology and Nutrition
Inflammatory Bowel Disease
article

Using machine learning to predict clinical remission with exclusive enteral nutrition in pediatric Crohn disease

Wael El‐Matary, Roberto Vega, R G Suarez Suarez, Anthony Otley, David R. Mack, Russell Greiner, Abdul Sattar Shaikh, Kevan Jacobson, Eileen Crowley, Colette Deslandres, Anne M. Griffiths, Jennifer deBruyn, Eytan Wine, Daniel G. McClement, Mary Sherlock, Hien Q. Huynh, T D Walters
article en

Abstract

Our models, based on accessible clinical features, were able to effectively predict EEN success above chance. This supports the plausibility of building clinical tools to assist precision therapy for pCD patients.

Journal of Pediatric Gastroenterology and NutritionVol. 82(2)
Western University (CA), Dalhousie University (CA), University of British Columbia (CA), University of Ottawa (CA), University of Alberta (CA), University of Calgary (CA), Children's Hospital of Eastern Ontario (CA), Centre Hospitalier Universitaire Sainte-Justine (CA), SickKids Foundation (CA), Children's Hospital of Western Ontario (CA), University of Manitoba (CA), Hamilton Health Sciences (CA), McMaster University (CA)
Openalex Percentile: Top 61%
Inflammatory Bowel Disease
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