CMU Researchers Open-Source ‘auton-survival’: A Comprehensive Python Code Repository of User-Friendly, Machine Learning Tools for Working with Censored Time-to-Event Data

Machine learning is being used in almost every industry, including healthcare. However, due to the intrinsic complexity of healthcare data, classical machine learning faces various difficulties while dealing with these data. This is because healthcare outcomes like mortality, stroke, cancer initiation, and readmission frequently have a continuous time to events. Since time-to-event data frequently contains individuals whose outcomes are missing or censored owing to loss of follow-up, dealing with this type of data is much more difficult. The researchers have …

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