Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

Systemic sclerosis (SSc) is a severe autoimmune disease with complex genetic causes. Some genetic contributors have been identified, but others remain unknown, which has impeded development of ...

A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...