CGMformer is first self-supervised pretrained on CGM data to gain fundamental knowledge of the glucose dynamics, and then applied to a multitude of downstream clinical applications. The extractable ...

Hepatocellular carcinoma patients with portal vein thrombosis treated with robotic radiosurgery for long term outcome and analysis: CTRT:2022/01/050234. This is an ASCO Meeting Abstract from the 2025 ...

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

A "deep learning" artificial intelligence model developed at Washington State University can identify pathology, or signs of disease, in images of animal and human tissue much faster, and often more ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

ICU patient monitoring forms the foundation for AI models to predict which sepsis patients will benefit from corticosteroid therapy, enabling personalized treatment decisions. Sepsis remains one of ...

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IIT Bhubaneswar study says deep learning model predicts Himachal, Uttarakhand cloudbursts up to 72 hours ahead, outperforming WRF in 2023 events.

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...