Machine-learning-informed simulations of physical phenomena ranging from drifting bands (left), resonant ripples (center) and ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Ligand Pro, founded by Skoltech professors and a Skoltech Ph.D. student, has presented Matcha, an AI-powered molecular docking model that performs virtual drug screening 30 times faster than the large ...

Background Hypertrophic cardiomyopathy (HCM) is associated with an increased risk of sudden cardiac death (SCD), and ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

To help solve this problem, Generalist has relied on “data hands,” a set of wearable pincers that capture micro-movements and ...

Artificial intelligence does not exist in a vacuum. Behind every well-trained model, every accurate recommendation engine, ...

Abstract: Machine learning (ML) models for disease diagnostics and prognostics have been widely used in medicine, leveraging real-world clinical data and benefiting both clinicians and patients.

Researchers have used artificial intelligence to predict dozens of previously unknown carbon crystal structures, including at ...

Regulatory pressure from GxP, 21 CFR Part 11, and AI/ML guidance elevates requirements for audit trails, data lineage, ...

Today I’d like to share with you an investigation we undertook related to ingesting Open Telemetry data in Elasticsearch, while maintaining tenant segregation from start to end. Let’s imagine we have ...

Minnesotans, after weeks of dealing with Immigration and Customs Enforcement, have developed strategies for dealing with the agency’s occupation of the city and now, Americans from across the country ...