We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, ...

A method was developed for discovering and validating therapeutically relevant patient subsets using a new paradigm on the basis of predictive classification rather than multiple hypothesis testing. A ...

We propose a united approach to maximum likelihood estimation, classification, and statistical learning in the context of finite mixture models, based on observations that can be considered a ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

In the ever-evolving field of clinical diagnostics, the fusion of disciplines often leads to groundbreaking advancements. As a statistician and a biomedical scientist, we have found a shared interest ...