The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

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 ...

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...

Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...

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.

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 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 ...