Machine Learning-Based Model to Predict Long-Term Tumor Control and Additional Interventions following Pituitary Surgery for Cushing's Disease.

This article discusses the use of a machine learning model to predict long-term tumor control and the need for additional interventions following pituitary surgery for Cushing's disease. The study analyzed data from patients who underwent endonasal transsphenoidal surgery (ETS) for Cushing's disease between 2013 and 2022. The results showed that Knosp-Steiner grade 4 cavernous sinus extension, tumor size, and patient age were the most significant predictors of intervention-free survival. These findings provide valuable insights into identifying at-risk patients who may require additional interventions in the future. [Extracted from the article]