Clinical Trials

The effectiveness of CBT-based NLP-enabled AI conversational agents for mental health intervention: a systematic review and meta-analysis.

Natural language processing (NLP)-enabled artificial intelligence (AI) conversational agents (CAs) are increasingly adopted in digital mental health interventions, yet the efficacy of such CAs grounded in cognitive behavioral therapy (CBT) remains unclear. This study aims to examine the intervention effectiveness of CBT-based NLP-enabled AI CAs in various mental health problems. A total of 15 rand...

General-purpose large language models outperform specialized clinical AI tools on medical benchmarks.

Specialized clinical artificial intelligence (AI) tools are entering medical practice despite scarce independent evaluation. We quantitatively evaluate two clinical AI tools, OpenEvidence and UpToDate Expert AI, built on large language models (LLMs) against three frontier LLMs: GPT-5.2, Gemini 3.1 Pro and Claude Opus 4.6. Our evaluation has three stages: (1) 500 MedQA questions testing medical kno...

Large language models for optimizing clinical trial recruitment in ICUs: application to ventilator-induced diaphragm dysfunction.

BACKGROUND: Ventilator-induced diaphragm dysfunction (VIDD) is a frequent and under-recognized consequence of prolonged mechanical ventilation in inte...

Applying machine-learning models to successful vaginal birth after two cesareans.

BACKGROUND: Vaginal birth after two cesarean deliveries (VBAC2) is increasingly recognized as a reasonable and, in selected cases, preferable option. ...

Mass cytometry reveals complex neutrophil heterogeneity in patients with severe sepsis.

RATIONALE: Sepsis is a state of life-threatening organ dysfunction in the setting of infection. It is biologically heterogeneous, as evidenced by whol...

Between Help and Harm: An Evaluation Study of Mental Health Crisis Handling by Large Language Models.

BACKGROUND: The use of large language models (LLMs)-powered chatbots has reshaped how people seek information and advice, including for emotional and ...

A multi-state methodological framework for behavioral surveillance of cannabis-impaired driving.

OBJECTIVES: Driving under the influence of cannabis is a growing public health concern in the United States. Existing surveillance systems often lack ...

Artificial intelligence in food safety.

Artificial Intelligence (AI) is revolutionizing many fields including food safety. In food safety, the available data generated within the agrifood sy...

Clinical artificial intelligence applications of vision-language foundation models.

Vision-language models (VLMs) represent a transformative advance in generative artificial intelligence (AI), using multimodal data processing to enhan...

Clinical implementation of artificial intelligence in adolescent mental healthcare.

PURPOSE OF REVIEW: This review aims to summarize recent literature on artificial intelligence (AI) tools for adolescent mental health, including the t...

PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction.

Immunotherapy has revolutionized cancer treatment, yet substantial inter-patient response heterogeneity limits therapeutic benefit to specific patient...

Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.

BACKGROUND: Large language models (LLMs) are increasingly explored as tools for medical education. However, evidence remains limited regarding their p...

Evaluating the quality of artificial intelligence responses to psoriasis-related clinical and patient questions: a comparative study of ChatGPT, Gemini, and Microsoft Copilot.

BACKGROUND: Patient use of artificial intelligence (AI) chatbots for dermatologic information is increasing, but their performance on psoriasis-relate...

Developmental circuit instability in amyotrophic lateral sclerosis: from hyperexcitability to network collapse.

Amyotrophic lateral sclerosis (ALS) is traditionally viewed as a late-onset motor neuron disease, yet how cortical dysfunction originates and contribu...

Pre-implementation safety evaluation of an AI decision-support system for surgical antimicrobial prophylaxis.

BACKGROUND: Large language models (LLMs) show potential to support antimicrobial prescribing but require simulation-based, institution-specific safety...

Large Language Models and Retrieval-Augmented Platforms for Dental Implant Complications: A Blinded, Expert-Rated Benchmarking Study.

OBJECTIVES: To compare expert-rated diagnostic accuracy, patient safety, completeness of management, and freedom from detectable hallucinations across...

The engagement-validation loop: Sycophancy, anthropomorphic projection, and clinical risk in informal AI-based mental health support.

Approximately one billion people worldwide live with a mental disorder, yet access to minimally adequate treatment remains low. Against this backdrop,...

Psychological safety and perceived risk are associated with emergency nurses' intention to use AI-augmented triage systems.

Emergency department overcrowding places sustained pressure on triage workflows and patient prioritization. Artificial intelligence (AI)-augmented tri...

Advances in Ultrasound-Guided Fascial Plane Blocks for Perioperative Acute Pain Management.

INTRODUCTION: Perioperative acute pain remains a major challenge because conventional analgesic strategies are often limited by inadequate efficacy an...

Global advances in health artificial intelligence: a workforce imperative.

The global health workforce is approaching a breaking point, driven by administrative overload, inefficient workflows, burnout, and accelerating retir...