Latest AI and machine learning research in clinical trials for healthcare professionals.
Background Community-wide active case-finding (ACF) is being increasingly implemented as a tuberculo...
Background: Professionalism and effective communication are foundational determinants of patient saf...
Accurate modeling of aerodynamic loads is essential for understanding and predicting the responses o...
Background Patients worldwide receive healthcare in many languages, yet medical AI systems are valid...
Rhythmic temporal structure improves working memory, but how this benefit emerges from recurrent dyn...
Background: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome...
Background: Large language models (LLMs) demonstrate strong performance in controlled medical enviro...
Background: Large language models (LLMs) are increasingly used in telehealth, but their safety in an...
Machine-learning surrogate models are positioned to help optimize deep brain stimulation (DBS) usage...
Randomized neural networks (RdNNs) enable efficient, backpropagation-free training by freezing rando...
Single-arm trials are an important study design for evaluating drug efficacy and safety without enro...
Drug-induced arrhythmias, particularly Torsades de Pointes (TdP), pose a significant risk to patient...
Red teaming is critical for uncovering vulnerabilities in Large Language Models (LLMs). While automa...
Background: Large language models (LLMs) are increasingly used in medical education and clinical dec...
The neuromodulator acetylcholine has been suggested to govern learning under uncertainty. Here, we i...
Explainable Artificial Intelligence (XAI) is increasingly rec ognized as essential for deploying mac...
We propose Conformal Seasonal Pools (CSP), a training-free probabilistic time-series forecaster that...
Clinical LLMs are often scaled by increasing model size, context length, retrieval complexity, or in...
The widespread adoption of machine learning in critical applications demands techniques to mitigate ...
Formal verification of neuro-symbolic cyber-physical systems, such as drones, medical devices and ro...
Frequent HIV testing, or "retesting," the practice of regular HIV testing following a negative test ...