2023/11/27 by Weiyi He, Weiyi, He
Computer Science · Medicine · #Applications (stat.AP) #FOS: Computer and information sciences #Machine Learning in Healthcare #Radiomics and Machine Learning in Medical Imaging
paper · pdf · doi:10.48550/arxiv.2311.15743
openalex publication_date 2023/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The accurate prediction of patient prognosis is a critical challenge in clinical practice. With the availability of various patient information, physicians can optimize medical care by closely monitoring disease progression and therapy responses. To enable better individualized treatment, dynamic prediction models are required to continuously update survival probability predictions as new information becomes available. This article aims to offer a comprehensive survey of current methods in dynamic survival analysis, encompassing both classical statistical approaches and deep learning techniques. Additionally, it will also discuss the limitations of existing methods and the prospects for future advancements in this field.