Deep Learning-Based Dynamic Risk Prediction of Venous Thromboembolism for Patients With Ovarian Cancer in Real-World Settings From Electronic Health Records Data collected in the multicentric PRAIS ...

Please provide your email address to receive an email when new articles are posted on . Explainable machine learning can offer accurate diagnoses and identify causes of chronic kidney disease in early ...

This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...

In a significant breakthrough, researchers have developed an advanced explainable deep learning model to predict and analyze harmful algal blooms (HABs) in freshwater lakes and reservoirs across China ...

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...

In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...

Scheduled in April in Rio de Janeiro, ICLR 2026 focuses on cutting-edge research on deep learning used in the fields of ...

There are three technical enablers “that repeatedly separate successful [AI] deployments from stalled pilots: trustworthy data pipelines, fit-for-purpose model selection, and lifestyle governance,” ...

Enterprise software is undergoing a major transformation as machine learning becomes deeply embedded into core digital ...