Personalized Prediction of Survival Rate with Combination of Penalized Cox Models and Machine Learning in Patients with Colorectal Cancer
Seon Hwa Lee,
Jae Myung Cha,
Seung Jun Shin
Abstract:Background
The investigation into individual survival rates within the patient population was typically conducted using the Cox proportional hazards model, with geometric black box models not being employed
Aims
We aims to evaluate the performance of machine learning algorithm in predicting survival rates more than 5 years for individual patients with colorectal cancer.
Methods
A total of 475 patients with CRC and complete data who had underwent surgery for colorectal cancer were analyze to measure individu… Show more
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