A multimodal sleep foundation model based on polysomnography data can predict the risk for multiple conditions, including dementia.
Zhipu claims GLM-Image achieved industry-leading scores among open-source models for text rendering and Chinese character ...
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 ...
News-Medical.Net on MSN
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 ...
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 ...
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 ...
2UrbanGirls on MSN
Secure data warehousing in ERP environments: An AI-based multimodal threat detection framework by Emmanuel Philip Nittala
In an era where data has become one of the most valuable assets for organizations, protecting that data is a strategic ...
Abstract: Advancing Multimodal AI for Integrated Understanding and Generation explores the transformative potential of multimodal artificial intelligence (AI), which integrates diverse data types such ...
First, multimodal imaging, demographic, and clinical data obtained from 90-d HDTBR experiment. Further statistical analyses were conducted for alteration of CBF. Next, the CBF prediction models were ...
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