A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A multi-class classification problem is one where the goal is to predict the ...

A new research paper featured on the cover of Volume 17, Issue 11 of Aging-US was published on October 30, 2025, titled "SAMP ...

Discover how random forests, a machine-learning technique, enhance prediction accuracy by combining insights from multiple ...

A study published in JAMA Network Open describes the utility of multi-level machine learning models in estimating the risk of delay between cancer diagnosis and treatment initiation in a large group ...

Model Development of CDK4/6 Predicted Efficacy in Patients With Hormone Receptor–Positive, Human Epidermal Growth Factor Receptor 2–Negative Advanced or Metastatic Breast Cancer Computed tomography ...

Researchers used machine learning to generate highly detailed maps of over 100 million individual trees from 24 sites across the U.S. These maps provide information about individual tree species and ...

A new field promises to usher in a new era of using machine learning and computer vision to tackle small and large-scale questions about the biology of organisms around the globe. A new field promises ...

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 ...