AI set to transform personality testing, new research finds

Personality tests are widely used in workplaces to shape recruitment, leadership training and team building. But what if ...
News-Medical.Net

Machine learning model predicts liver cancer risk with high accuracy

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...
Tech Xplore

Researchers use machine learning and social network theory to identify formation patterns in digital forums

Researchers at Stevens Institute of Technology used machine learning tools and social network theory—the study of how people ...

A machine learning model may enable liver cancer risk prediction with routine clinical information

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
Tech Xplore on MSN

AI can flag high-risk motorists before getting on the road, scientists say

Scientists at the University of Sharjah have developed a new machine learning model capable of predicting whether a driver is likely to be involved in an accident before getting behind the wheel. Road ...
Scientific Research Publishing

A Multimodal Machine-Learning Framework for Predicting Lithium-Associated Renal Dysfunction from Synthetic Biomarker Trajectories ()

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant ...
The New York Times

Employment Commission Says Agencies Can Restrict Bathroom Use by Sex

The ruling extends the Equal Employment Opportunity Commission’s intervention on President Trump’s gender and race priorities. By Rebecca Davis O’Brien The Equal Employment Opportunity Commission said ...
The Lancet

When to and when not to use machine learning in risk prediction models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
IEEE

Gender Classification Based on Machine Learning Models

Abstract: Automatic gender categorization has become an increasingly significant area in computer vision, with several applications. Gender equality is nowadays a keyword for today's scenario. This ...