Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the ...

Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level relationships between patient characteristics and cancer outcomes. Machine learning ...

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...

Leveraging Centralized Health System Data Management and Large Language Model–Based Data Preprocessing to Identify Predictors for Radiation Therapy Interruption This study presents a new method based ...

Current models of motivation and cognitive control have relied to a large extent on the Reinforcement Learning framework. While this approach has enjoyed considerable success, other frameworks may ...