A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
Pediatric hospital medicine is rapidly advancing with new research focusing on clinical management, quality improvement, health equity, and technology. This summary highlights the top articles from ...
Machine learning (ML) models now influence decisions that were once reserved solely for human judgement: credit approvals, hiring outcomes, insurance pricing, and loan default predictions. When these ...
Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...
A new algorithm could drive breakthroughs in understanding cancer, Alzheimer's disease and other potentially fatal conditions ...
ZoomInfo's verified company, contact, and signal data now flows natively into the Databricks lakehouse through GTM.AI, so every model, score, ...
Mayo Clinic plans to develop and deploy a frontier AI model specifically designed for healthcare in collaboration with Microsoft. The strategic collaboration combines Mayo Clinic’s global healthcare ...
A retrospective study of donafenib with or without TACE as postoperative adjuvant therapy for hepatocellular carcinoma (HCC) patients at high risk of recurrence after radical resection. This is an ...
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