Researchers awarded $10.5 million to study use of AI in addressing cardiovascular disease
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Updates every hour. Last Updated: 2-Jan-2026 16:11 ET (2-Jan-2026 21:11 GMT/UTC)
A new theory-guided framework could help scientists probe the properties of new semiconductors for next-generation microelectronic devices, or discover materials that boost the performance of quantum computers.
Mathematics may not be the first thing people associate with Alzheimer’s disease research. But for Pedro Maia, an assistant professor of mathematics and data science at The University of Texas at Arlington, analyzing how different parts of the brain interact like a network is revealing new insights into one of the world’s most devastating brain disorders.
For the first time, the James Webb Space Telescope has observed several tidal disruption events — when a black hole draws in a nearby star and tears it to shreds. Surprisingly, these are not active black holes, but rather dormant ones that briefly “wake up” to feast on a passing star.
This study assessed the diagnostic accuracy and fairness of multimodal large language models (ChatGPT-4 and LLaVA) in identifying skin diseases across various demographic groups. Analysis of approximately 10,000 medical images showed that while these AI models generally outperform traditional approaches, biases in performance related to sex and age were evident, particularly with LLaVA showing clear sex-related disparities.
Researchers advocate for attention to demographic fairness in AI-driven healthcare solutions. Further studies are planned to include additional demographic factors such as skin tone, aiming to enhance AI usability and reliability across diverse patient populations.