Which model is better in predicting the survival of laryngeal squamous cell carcinoma?: Comparison of the random survival forest based on machine learning algorithms to Cox regression: analyses based on SEER database

• Published in: Medicine (Baltimore) Vol. 102; no. 10; p. e33144
• Main Authors: Sun, Haili, Wu, Shuangshuang, Li, Shaoxiao, Jiang, Xiaohua
• Format: Journal Article
• Language: English
• Published: United States Lippincott Williams & Wilkins 10.03.2023
• Subjects: Algorithms; Head and Neck Neoplasms; Humans; Machine Learning; Observational Study; Random Forest; Squamous Cell Carcinoma of Head and Neck

Prediction of postoperative survival for laryngeal carcinoma patients is very important. This study attempts to demonstrate the utilization of the random survival forest (RSF) and Cox regression model to predict overall survival of laryngeal squamous cell carcinoma (LSCC) and compare their performan...