ArticleWorld journal of gastrointestinal surgery2024
Machine learning as a tool predicting short-term postoperative complications in Crohn's disease patients undergoing intestinal resection: What frontiers?
Article in World journal of gastrointestinal surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Genetic and environmental factors influencing Crohn's disease.World journal of gastrointestinal surgery · 2025Article
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Abstract
The recent study, "Predicting short-term major postoperative complications in intestinal resection for Crohn's disease: A machine learning-based study" investigated the predictive efficacy of a machine learning model for major postoperative complications within 30 days of surgery in Crohn's disease (CD) patients. Employing a random forest analysis and Shapley Additive Explanations, the study prioritizes factors such as preoperative nutritional status, operative time, and CD activity index. Despite the retrospective design's limitations, the model's robustness, with area under the curve values surpassing 0.8, highlights its clinical potential. The findings align with literature supporting preoperative nutritional therapy in inflammatory bowel diseases, emphasizing the importance of comprehensive assessment and optimization. While a significant advancement, further research is crucial for refining preoperative strategies in CD patients.
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