Clinical Trials

Leveraging artificial intelligence to accelerate competency development in diagnostic reasoning of medical students.

INTRODUCTION: Diagnostic errors remain a critical patient safety concern, yet teaching diagnostic reasoning is challenging due to its complex, context-specific nature. Traditional teaching methods emphasize analytical reasoning but often neglect non-analytical, pattern recognition processes that are grounded in script theory. Script theory highlights illness scripts-structured mental representatio...

Mirror Descent Safe Policy Optimization for Reinforcement Learning Agents.

Embodied intelligence and related disciplines have identified several mechanisms that help embodied agents learn how to solve complex problems. Reinforcement learning (RL) is one of the most promising computational approaches toward enhancement of the learning-based problem-solving abilities of such agents. Given the recent rapid evolution of artificial intelligence, RL has become a keystone techn...

Integrating Large Language Models Into Trauma Education for Medical Students: Randomized Controlled Pilot Trial.

BACKGROUND: The exponential growth of medical knowledge presents a paradox for modern medical education. While access to information is immediate, app...

Molecular and Pharmacogenetic Marker Evaluation in Relation to the Toxicity and Clinical Response of Acute Lymphoblastic Leukemia Treatment in Indian Children (MPGx-INDALL): Protocol for a Prospective Observational Cohort Study.

BACKGROUND: Understanding interindividual variability in treatment response and toxicity is essential for optimizing outcomes in pediatric acute lymph...

Illuminating the black box of traditional Chinese medicine: The pivotal role of transgenic fluorescent zebrafish.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) holds significant therapeutic potential, yet its modernization is hindered by the i...

Disclaimers and Referral Patterns for Medical Advice Across Urgency Levels: Large Language Model Evaluation Study.

BACKGROUND: "I'm not a doctor, but..." is a typical response when asking considerate laypeople for health advice. However, seeking medical advice has ...

Drug repurposing in oncology: Bridging computational discovery to clinical application.

Drug repurposing, the identification of new therapeutic applications for existing drugs, has emerged as a pragmatic and cost-efficient strategy to acc...

Relying on AI at work reduces self-efficacy, ownership, and meaning while active collaboration mitigates the effects.

Artificial intelligence (AI) promises major productivity gains, but it also raises fundamental questions about how technology can reshape people's rel...

The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations.

Integrating artificial intelligence (AI) into maternal and neonatal health (MNH) offers significant opportunities for enhancing patient care through a...

Individualized treatment effects of CPAP on secondary cardiovascular outcomes in non-sleepy obstructive sleep apnea patients.

BACKGROUND: Continuous positive airway pressure (CPAP) remains the cornerstone of therapy for obstructive sleep apnea, yet its impact on preventing ca...

Artificial intelligence and the future of inflammatory bowel disease trial recruitment: from bottleneck to breakthrough.

Novel cooking techniques and their impact on livestock meat quality: A comprehensive review of processing, eating, nutritional, and safety quality.

Traditional meat cooking methods, such as boiling, frying, and grilling, often lead to nutrient loss, reduced flavor, and microbiological safety risks...

Advancing Global Drug Safety: Challenges and Future Perspectives in Pharmacovigilance.

Adverse Drug Reactions (ADRs) pose significant challenges to patient safety, healthcare systems, and public health worldwide. As the pharmaceutical la...

Language-Related Functional Connectivity in Post-Stroke Aphasia: Preliminary Findings from a Graph-Theoretical and Interpretable Machine Learning Study.

PURPOSE: To have an insight into language-related functional connectivity in post-stroke aphasia (PSA) from graph theory measurements when performing ...

Advancing cell and gene therapy: Application of AI/ML in clinical development and patient management.

This article explores the transformative potential of artificial intelligence (AI) and machine learning (ML) in advancing cell and gene therapy (CGT) ...

Trustworthy AI-Augmented Objective Structured Clinical Examinations in Nursing Education: Taiwan-Japan Viewpoint on 5 AI Roles, Governance, and Cross-Border Implementation.

Generative artificial intelligence (AI) is arriving in high-stakes assessment; however, governance, validity evidence, and faculty readiness remain un...

Strategic Governance of Artificial Intelligence-Enabled Clinical Algorithm Development: Formative Evaluation of the Semiautomatic Clinical Algorithm Development Framework.

BACKGROUND: Health care leaders face a strategic dilemma: traditional expert-led content development ensures safety but is too slow for digital innova...

Multimodal MRI radiomics for predicting HIFU ablation efficacy in uterine fibroids: a machine learning study.

OBJECTIVE: To explore the predictive value of machine learning-based multimodal MRI radiomics combined with clinical features in the efficacy of high-...

NeuroMix-DL: Improving imaging quality of a fast multiparametric MRI protocol using deep learning.

PURPOSE: To improve the quality of a fast multi-contrast MR protocol acquisition using deep learning. MATERIALS AND METHODS: 350 patients (age: 64 ± 1...

A machine learning based scheme for enhancing the detection of position falsification attacks in vehicular ad hoc networks.

Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and their surrounding infrastructure, enabling the exchange of i...