Google's TabFM skips per-dataset training and still predicts on tables it's never seen

Google's TabFM skips per-dataset training and still predicts on unseen tables, matching tuned baselines and cutting pipeline ...

Researchers develop low-cost AI tool to help cities map urban tree canopy

As a heat dome drives dangerous temperatures across much of the United States and renews concerns about extreme heat, USC ...

Study raises concerns about AI health-prediction models trained on unreliable datasets

Some AI models designed to predict stroke and diabetes risk may be based on datasets whose origins cannot be verified, ...
Visual Studio Magazine

Random Forest Regression Using C#

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...
Sports Illustrated

Wake Forest vs. Virginia Prediction, Odds for College Basketball on Tuesday, March 3

The No. 13 Virginia Cavaliers have a great opportunity to bounce back from a road loss against Duke when they host the Wake Forest Demon Deacons on Tuesday night. Virginia had a nine-game winning ...
Frontiers

Web-based cardiovascular disease risk prediction using machine learning

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates Random Forest ...
The Lancet

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

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
Frontiers

Early prediction of gestational diabetes mellitus using machine learning-integrated metabolomic and clinical features

Gestational diabetes mellitus (GDM), a prevalent metabolic disorder associated with pregnancy, which often postpones intervention until after metabolic complications have developed. This study seeks ...