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 ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

Predictive Model of Acute Rectal Toxicity in Prostate Cancer Treated With Radiotherapy This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, ...

Scientists have created an AI model that forecasts moderate heat stress — a major precursor to coral bleaching — at sites along Florida's ...

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, ...

The reason for this shift is simple: data gravity. The core holds the most complete, consistent and authoritative dataset available to the institution. Moving AI decisioning closer to this data ...