Isomorphic Lab’s proprietary drug-discovery model is a major advance, but scientists developing open-source tools are left ...
Morning Overview on MSN
Scientists grew mini brains and trained them to crack an engineering problem
Researchers at the University of California, Santa Cruz have trained lab-grown brain organoids to solve a goal-directed task, ...
The evolution of AI-powered vehicle inspection has moved rapidly from experimental research to an essential pillar of the modern automotive ecosystem. Historically, vehicle checks were manual and ...
The March 2026 issue of NEJM Catalyst Innovations in Care Delivery is a special theme issue on the hard work of implementing artificial intelligence in real-world ...
With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...
University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a groundbreaking new resource that could accelerate drug development for ...
To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.
Explore how machine learning in insurance enhances risk assessment, fraud detection, and personalization. ✓ Subscribe for ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
Abstract: Reliable uncertainty estimation has become a crucial requirement for the industrial deployment of deep learning algorithms, particularly in high-risk applications such as autonomous driving ...
Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...
Abstract: Learning to optimize and automated algorithm design are attracting increasing attention, but it is still in its infancy in constrained multiobjective optimization evolutionary algorithms ...
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