Rapid advances in artificial intelligence, machine learning, and data-driven computational modeling have opened unprecedented opportunities to transform ...

Choosing the right method for multimodal AI—systems that combine text, images, and more—has long been trial and error. Emory ...

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.

Stina Saunders, PhD, Personalized Medicine Lead at Linus Health, will present new data exploring how culturally responsive, person-specific outcome measures can be scaled across international ...

In the rapidly evolving realm of genetics, the integration of artificial intelligence (AI) has ushered in new perspectives on therapeutic approaches and evolutionary processes. Traditional genetic ...

WASHINGTON, DC, UNITED STATES, March 2, 2026 /EINPresswire.com/ -- Designing Enterprise AI Systems, Governance ...

The Multimodal Education Center (MEC) is a university-wide program that enables students and faculty to engage in science, technology, engineering, and mathematics (STEM). “[The MEC] is a hub of ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

Studying gene expression in a cancer patient's cells can help clinical biologists understand the cancer's origin and predict the success of different treatments. But cells are complex and contain many ...

Multimodal sensing in physical AI (PAI), sometimes called embodied AI, is the ability for AI to fuse diverse sensory inputs, ...

Researchers have proposed a multimodal sensor fusion approach to AI-based fault detection in 3D printing, aiming to push AM monitoring closer to reliable, Industry 4.0 operation.

The partnership integrates high-resolution multi-omics data generation with predictive multimodal machine learning to support biopharma decision-making in neurology.