Interpretable personalized surgical recommendation with joint consideration of multiple decisional dimensions.

ABSTRACT: Surgical planning can be highly complicated and personalized, where a surgeon needs to balance multiple decisional dimensions including surgical effectiveness, risk, cost, and patient's conditions and preferences. Turning to artificial intelligence is a great appeal. This study filled in this gap with Multi-Dimensional Recommendation (MUDI), an interpretable data-driven intelligent system that supported personalized surgical recommendations on both the patient's and the surgeon's side with joint consideration of multiple decisional dimensions. Applied to Pelvic Organ Prolapse, a common female disease with significant impacts on life quality, MUDI stood out from a crowd of competing methods and achieved excellent performance that was comparable to top urogynecologists, with a transparent pr

SUBMITTER: Du Z 

PROVIDER: S-EPMC11923295 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature