all AI news
A review on longitudinal data analysis with random forest in precision medicine. (arXiv:2208.04112v1 [stat.ML])
cs.LG updates on arXiv.org arxiv.org
Precision medicine provides customized treatments to patients based on their
characteristics and is a promising approach to improving treatment efficiency.
Large scale omics data are useful for patient characterization, but often their
measurements change over time, leading to longitudinal data. Random forest is
one of the state-of-the-art machine learning methods for building prediction
models, and can play a crucial role in precision medicine. In this paper, we
review extensions of the standard random forest method for the purpose of
longitudinal …
analysis arxiv data data analysis medicine ml precision precision medicine random review