A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...
The American Heart Association and Laerdal Medical further commitment to provide equitable, increased access to high-quality ...
A peer-reviewed article in Neurobiology of Learning and Memory is challenging a foundational assumption about how animals and humans form associations between cues and rewards, Rather than relying ...
A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to ...
A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...
Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient’s risk of hepatocellular carcinoma (HCC), the most common ...
Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.
The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...
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 ...
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