Construction and Validation of a Long‐Term Visual Prognosis Prediction Model for Proliferative Diabetic Retinopathy After Vitrectomy Based on Machine Learning
This study aims to develop a machine‐learning‐based risk prediction model for a long‐term visual prognosis in patients with proliferative diabetic retinopathy (PDR) following pars plana vitrectomy (PPV).
Pulmonary metastasis in high‐grade conventional osteosarcoma remains a leading cause of treatment failure and mortality. Traditional monitoring methods are insufficient for early detection. This study aims to develop and validate an interpretable machine learning (ML) model using multi‐dimensional data from electronic...
Jian-Hua Mu, Yi-Tian Wang, Han Liu et al.· Cancer Medicine· 0 citations
Machine learning models, particularly XGBoost, provide robust risk stratification for high-risk neonates and can complement existing programs by identifying high-risk infants who require prioritized diagnostic follow-up and closer clinical monitoring.
Sevgi Kutlu, Emre Söylemez, Betül Temir et al.· The Laryngoscope· 0 citations
Predicting clear cell renal cell carcinoma (ccRCC) pathological grade preoperatively is critical for clinical management. This study aims to evaluate the diagnostic accuracy and clinical utility of machine learning (ML)‐based imaging models.
Yu-Chao Wang, Zhu-Wei Song, Zhaonan Hou et al.· Cancer Medicine· 0 citations
