A Simulation Study to Compare the Predictive Performance of Survival Neural Networks with Cox Models for Clinical Trial Data.
Journal:
Computational and mathematical methods in medicine
PMID:
34880930
Abstract
BACKGROUND: Studies focusing on prediction models are widespread in medicine. There is a trend in applying machine learning (ML) by medical researchers and clinicians. Over the years, multiple ML algorithms have been adapted to censored data. However, the choice of methodology should be motivated by the real-life data and their complexity. Here, the predictive performance of ML techniques is compared with statistical models in a simple clinical setting (small/moderate sample size and small number of predictors) with Monte-Carlo simulations.
Authors
Keywords
Algorithms
Bone Neoplasms
Clinical Trials as Topic
Clinical Trials, Phase III as Topic
Computational Biology
Computer Simulation
Data Interpretation, Statistical
Female
Humans
Machine Learning
Male
Neural Networks, Computer
Osteosarcoma
Prognosis
Proportional Hazards Models
Randomized Controlled Trials as Topic