Clinical Trials

Exploring stress and coping among black women in early midlife with elevated blood pressure in a safety-net health system: a qualitative focus group protocol.

INTRODUCTION: Black women in early midlife experience disproportionate exposure to stress and elevated cardiovascular risk, including hypertension. Despite this, few stress management interventions are designed with and for this population. This study aims to explore the lived experiences of stress and coping among black women in early midlife with elevated blood pressure to inform the codesign of...

Machine learning methods to evaluate fluctuation in oxygenation and peripheral tissue temperature, in sacral and trochanteric area under pressure in healthy subjects and institutionalized patients. A prospective non-randomized trial.

AIM: To evaluate the longitudinal changes observed over a period of 120 min in patterns of tissue perfusion, peripheral oxygenation and local temperature of sacral and trochanteric areas exposed to pressure, comparing a healthy population with one at risk of impaired skin integrity. METHODS: The study protocol is registered in ClinicalTrials.gov (NCT02736838). Non-randomised experimental study in ...

The chemical design of antimicrobial ionic liquids guided by machine learning: a review on balancing efficacy and toxicity.

The design of new antimicrobial materials is a critical challenge in chemistry and materials science, driven by the global threat of multidrug-resista...

Flexible Coupling of Synaptic and Intrinsic Plasticity in a Cerebellar Circuit.

It is increasingly recognized that learning and memory depend, not only on changes in synaptic strength, but also on experience-dependent modification...

Breaking through safety performance stagnation in autonomous vehicles with dense learning.

Autonomous vehicles remain commercially limited largely due to safety performance stagnation. Existing deep learning, heavily reliant on failure data ...

Clinical AI Applications in the Context of Cancer: Explaining Openness to Information and Consent to Use Through Risk Perceptions and Efficacy Beliefs.

The use of artificial intelligence (AI) in oncology holds immense potential for improving diagnostic accuracy and treatment outcomes. Yet, concerns ab...

A machine learning model integrating circulating Temra cell transcriptional profiles to predict immunotherapy efficacy.

BACKGROUND: While immunotherapy has transformed treatment paradigms for cancer, durable response rates remain below 30%. Currently available biomarker...

Effectiveness of transcranial direct current stimulation (tDCS) on attention and memory biases in individuals with post-traumatic stress disorder (PTSD): a randomized, single-blind, parallel-group study.

Based on neurocognitive models, the development and maintenance of post-traumatic stress disorder (PTSD) are correlated with cognitive biases, includi...

From conventional screening to self-driving discovery: Organ-on-Chip platforms as engines for AI-guided nanomedicine.

Nanoparticles have become an essential platform for next-generation drug delivery and therapeutic development, yet clinical translation remains limite...

Taiwan Academy of Tumor Ablation (TATA) consensus on hepatocellular carcinoma ablation.

Hepatocellular carcinoma (HCC) ranks sixth in incidence and third in mortality worldwide, underscoring its public health burden. Ablation therapy is o...

Predicting Hypertension Persistence in Coarctation of the Aorta: A Feasibility Study.

Hypertension (HTN), despite contemporary endovascular repair, is a common and challenging complication of coarctation of the aorta (CoA), and its mech...

Enhanced Identification of Chronic Ankle Instability Under Different Conditions: A New Evaluation Framework Based on Feature Fusion and Machine Learning.

This study proposed a synergy-informed evaluation framework that integrates muscle synergy features derived from non-negative matrix factorization (NN...

Artificial intelligence-based image recognition in bronchoscopy: software development and randomized controlled trial for training evaluation in intensive care residents.

Comparison of large language models for clinical scenario generation in medical education: a mixed-methods study.

BACKGROUND: In undergraduate medical education, the ability to manage clinical-cases is a core competency expected of future physicians. Traditionally...

CodeSafetyBench evaluating and improving ethical safety in large language model code generation.

As large language models transform software development, they introduce significant ethical and safety risks, with research revealing a 78.67% probabi...

Is the FDA regulation of cardiology AI devices supporting cardiovascular innovation: a scoping review.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have shown immense potential in cardiology, leveraging data-driven insights to enha...

Assessing Artificial Intelligence in Breast Imaging: A Survey of Breast Radiologists' Insights on Adoption, Benefits, and Challenges.

OBJECTIVE: To evaluate radiologists' opinions on the clinical applications of artificial intelligence (AI), especially AI-based computer-aided detecti...

Can AI write reports like a radiologist? A blinded evaluation of large language model-generated lumbar spine MRI reports.

BACKGROUND: To compare the quality and clinical usefulness of large language model (LLM)-generated lumbar spine magnetic resonance imaging (MRI) repor...

Bias-Mitigated AI as a Foundation for Resilient and Effective Health Systems.

Artificial intelligence (AI) is rapidly reshaping the landscape of health care, from clinical diagnostics and disease surveillance to the prediction o...

Explaining the Slow Adoption of AI Innovations in Health Care: Network Analysis Approach.

BACKGROUND: Artificial intelligence (AI) is a topic of considerable hype, with many actors sensing its high potential for health care applications. De...