Interpretable Machine Learning –Based Prediction of Intraoperative Cerebrospinal Fluid Leakage in Endoscopic Transsphenoidal Pituitary Surgery: A Pilot Study

Conclusion A RF model that reliably identifies patients at risk for IOL was successfully trained and internally validated. ML-based prediction models can predict events that were previously judged nearly unpredictable; their deployment in clinical practice may result in improved patient care and reduced postoperative morbidity and healthcare costs. [...] Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, GermanyArticle in Thieme eJournals: Table of contents  |  Abstract  |  Full text

Source: Journal of Neurological Surgery Part B: Skull Base - January 16, 2022 Category: Neurosurgery Authors: Mattogno, Pier Paolo Caccavella, Valerio M. Giordano, Martina D'Alessandris, Quintino G. Chiloiro, Sabrina Tariciotti, Leonardo Olivi, Alessandro Lauretti, Liverana Tags: Original Article Source Type: research