BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
ascopubs.org

Optimizing Strategy for Lung Cancer Screening: From Risk Prediction to Clinical Decision Support

Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the ...
Visual Studio Magazine

Binary Classification Using a scikit Decision Tree

For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, income and political leaning. There are many other techniques for binary ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Visual Studio Magazine

Multi-Class Classification Using a scikit Decision Tree

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...