Seoul National University Hospital researchers have developed an AI model that predicts the response to an anticonvulsant ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
(NASDAQ: NXXT ), a pioneer in AI-driven energy innovation transforming how energy is produced, managed, and delivered, today ...
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
However, the absence of validated predictive models remains a significant challenge. Objective: This study compared a conventional logistic regression model with machine learning (ML) models using ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
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