Machine learning model predicts protein binding on gold nanoclusters

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

Neel Somani on How Privacy-Preserving Machine Learning Is Changing the Digital Landscape

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
European Medical Journal

Machine Learning Shows Promise in Predicting RA Treatment Response

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

Accelerating drug combination discovery with machine learning

Discovering effective drug combinations may now be easier thanks to a screening platform made public today by St. Jude ...
Devdiscourse

Financial institutions turn to adaptive AI to close fraud detection gaps

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...
EurekAlert!

Beyond small data limitations: Transfer learning-enabled framework for predicting mechanical properties of aluminum matrix composites

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
Electronics360

3 areas where AI lives in the electronics manufacturing stack

Today, AI is covering the whole stack of data analysis-based applications, starting at the wafer level and culminating in PCB assembly. Once a design is in assembly, AI primarily makes way into ...

Science vs. suspicion and fear: An Open Letter to a critic of Socialism AI

This is an Open Letter responding to several harsh criticisms of Socialism AI posted by Professor Tony Williams in the ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
News-Medical.Net on MSN

Machine learning reveals dental caries heterogeneity in NHANES

A new article published in the Journal of Dental Research explores the development an integrated data-cleaning and subtype discovery pipeline using unsupervised machine learning for comprehensive ...