A predictive machine-learning model for clinical decision-making in washed microbiota transplantation on ulcerative colitis.

ABSTRACT: Machine learning based on clinical data and treatment protocols for better clinical decision-making is a current research hotspot. This study aimed to build a machine learning model on washed microbiota transplantation (WMT) for ulcerative colitis (UC), providing patients and clinicians with a new evaluation system to optimize clinical decision-making. Methods Patients with UC who underwent WMT via mid-gut or colonic delivery route at an affiliated hospital of Nanjing Medical University from April 2013 to June 2022 were recruited. Model ensembles based on the clinical indicators were constructed by machine-learning to predict the clinical response of WMT after one month. Results A total of 366 patients were enrolled in this study, with 210 patients allocated for training and

SUBMITTER: Zhang S 

PROVIDER: S-EPMC11399476 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature