Machine Learning for Survival Analysis: A Survey

Understand

Accurately predicting the time of occurrence of an event of interest is a critical problem in longitudinal data analysis.

• One of the main challenges in this context is the presence of instances whose event outcomes become unobservable after a certain time point or when some instances do not experience any event during the monitoring period.
• Such a phenomenon is called censoring which can be effectively handled using survival analysis techniques.
• Traditionally, statistical approaches have been widely developed in the literature to overcome this censoring issue.