Summary Large Language Models (LLMs) are a key component of generative artificial
intelligence (AI) applications for creating new content including text, imagery, audio, code …

Sepsis is a common complication of combat injuries and trauma, and is defined as a life-
threatening organ dysfunction caused by a dysregulated host response to infection. It is also …

The personalized titration and optimization of insulin regimens for treatment of type 2
diabetes (T2D) are resource-demanding healthcare tasks. Here we propose a model-based …

In the past decade, the application of machine learning (ML) to healthcare has helped drive
the automation of physician tasks as well as enhancements in clinical capabilities and …

Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …

Background Interest in the application of machine learning (ML) to the design, conduct, and
analysis of clinical trials has grown, but the evidence base for such applications has not …

Objective To report the improvements achieved with clinical decision support systems and
examine the heterogeneity from pooling effects across diverse clinical settings and …

Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis,
which is critical in reducing mortality, is challenging as many of its signs and symptoms are …

Big data, high-performance computing, and (deep) machine learning are increasingly
becoming key to precision medicine—from identifying disease risks and taking preventive …

An emphasis on overly broad notions of generalisability as it pertains to applications of
machine learning in health care can overlook situations in which machine learning might …