A multimodal sleep foundation model based on polysomnography data can predict the risk for multiple conditions, including dementia.
Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
Trends in immune-related adverse event reporting among multidisciplinary cancer programs. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full ...
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AI trained on sleep data predicts future disease and mortality years in advance
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Abstract: Advancing Multimodal AI for Integrated Understanding and Generation explores the transformative potential of multimodal artificial intelligence (AI), which integrates diverse data types such ...
Pancreatic cancer mortality trends (2018-2023): Exposing racial inequities in Michigan's cancer burden. AUC for the PurIST baseline, the top 2 unimodal models, and the best fusion model for each ...
See how machine learning is spotting Alzheimer’s years before symptoms begin—using brain scans to help guide earlier, more ...
According to the paper, artificial intelligence addresses a core weakness in Parkinson’s care: reliance on subjective ...
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