aceDevelopment and external validation of an explainable machine-learning model for early complications following robot-assisted radical prostatectomy: a multicenter study
Complications occurring early after robot-assisted radical prostatectomy (RARP) can hinder postoperative recovery. Existing risk instruments, however, generally incorporate few predictors and assume linear associations. We aimed to derive and externally validate an interpretable machine-learning model that combines clinical, laboratory, and intraoperative information and to translate the model into an online risk calculator. Records were reviewed for 1,254 patients with prostate cancer (PCa) who received RARP at…
A multilayer perceptron using eight clinical, laboratory, and intraoperative predictors estimated early complication risk after prostatectomy, and an online calculator could help flag high-risk patients right after surgery.
The comparison with the Comorbidity Score for Robotic Surgery was described as exploratory and done only in the external cohort, so the evidence of superiority over existing tools is preliminary.
Evidence
- Peer-reviewedJournal of Robotic Surgery2026-10-01
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Truvace Impact Record TRV-2026-1485, v1: “Development and external validation of an explainable machine-learning model for early complications following robot-assisted radical prostatectomy: a multicenter study.” Truvace, 2026-10-15. /record/TRV-2026-1485 (accessed at citation time). sha256 e4e0033ca43a847a…
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