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 ...

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 ...

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...

Artificial intelligence (AI) and machine learning (ML) are revolutionizing the way we understand and predict soil processes. Yet, while data-driven models ...

How AI, privacy-preserving computation, and explainable models quietly strengthen payments, protect data, and bridge traditional finance with crypto systems.

This issue of The Journal of Risk Model Validation features two papers that directly address validation using machine learning. Whether their findings imply we will all (including the editor) become ...

The researchers also argue that explainable AI models are essential for ensuring fairness and accountability in policy design. In traditional statistical models, the relationships between variables ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.