Clinical Trials

Personalized Treatment Selection for Digital Eating Disorder Interventions: A Proof-of-Concept for the Personalized Advantage Index.

OBJECTIVE: Although a range of evidence-based treatments for eating disorders exist, treatment response varies substantially. The ability to match individuals to a treatment which they are most likely to benefit from may help improve treatment efficiency and therapeutic outcomes. The present study applies a treatment selection approach called the personalized advantage index (PAI) and evaluates it...

Therapeutic ultrasound in ophthalmology: a comprehensive review.

BACKGROUND: Therapeutic ultrasound has emerged as a promising noninvasive or minimally invasive modality in ophthalmology, offering novel solutions across a range of ocular disorders. This review summarizes the current advances in both the underlying biophysical mechanisms and their translation into clinical and experimental applications. METHODS: This review synthesizes and analyzes the current l...

Comparison of AI-assisted and human-produced podcasts derived from Cochrane Plain Language Summaries: protocol for a randomised non-inferiority trial (Health Information Effectiveness Trials-2).

BACKGROUND AND OBJECTIVES: Podcasts can make health evidence easier to follow, but it is unclear whether artificial intelligence (AI)-assisted product...

Whole genome sequencing precision medicine strategy to shorten treatment for rifampicin-resistant tuberculosis (SMARTT): a pragmatic, randomised, single-blind phase 4 trial.

BACKGROUND: All patients with rifampicin-resistant tuberculosis should receive a short course of effective treatment. We aimed to evaluate the effecti...

Equity, diversity, and inclusion: variations in clinical and academic radiology.

Equity, diversity, and inclusion (EDI) are fundamental to achieving fairness and representation in radiological research and practice. This review aim...

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures.

BACKGROUND: Treatment-as-usual (TAU) conditions are intended to reflect the support typically received in routine treatment settings. For digital ment...

Perceptions of Health Care Professionals on the Integration and Use of AI in Clinical Cancer Care: Interview Study.

BACKGROUND: Artificial intelligence (AI) is increasingly recognized for its potential to transform cancer care. However, much of the existing evidence...

Particle peak velocity prediction based on risk-oriented hybrid ensemble learning.

In blasting engineering, accurate prediction of peak particle velocity (PPV) is essential to ensuring the safety of surrounding structures. In machine...

Large language model-assisted radiology reporting in a single-radiologist implementation: a retrospective cohort study interpreted through a UTAUT lens.

BACKGROUND: Radiologist burnout affects approximately 40% of US radiologists. Large language models (LLMs) may improve workflow efficiency, but real-w...

DisenKGE-DDI: A Knowledge Graph Embedding Framework Based on Disentangled Graph Attention Networks for Drug-Drug Interaction Prediction.

Combination therapy is an essential strategy for treating complex diseases. However, unintended drug-drug interactions (DDIs) can compromise therapeut...

Low-light driver drowsiness detection for real-time safety assistance using dual attention mechanisms in deep learning model.

This research presents a robust real-time driver drowsiness detection system employing deep learning, attention mechanisms, and explainable AI (XAI) t...

A Review on Food Safety Analysis Based on Spectroscopic Techniques and Machine Learning.

In recent years, the integration of spectroscopic techniques with machine learning algorithms has emerged as a powerful analytical paradigm, demonstra...

The effect of an artificial intelligence-assisted motivational procedure on kinesiophobia and mobility after total knee arthroplasty: a randomized controlled trial.

Physics-informed deep learning for rapid marine radionuclide dispersion forecasting in nuclear emergency response.

In the event of a severe nuclear accident at a coastal nuclear power plant, the rapid and accurate assessment of radionuclide dispersion in surroundin...

AI in design education: Factors affecting students' professional learning adaptability.

Against the backdrop of accelerated reconstruction of the design-education ecosystem by artificial intelligence, this study focuses on the core issue ...

Artificial intelligence (AI)-assisted ultrasound in clinical trials: Endpoint automation, decentralized monitoring, and regulatory readiness.

Ultrasound is among the most widely used imaging modalities in clinical trials, and yet its dependence on operator skill and equipment settings has hi...

Optimal treatment selection for hepatocellular carcinoma in the era of immunotherapy.

Immunotherapy has revolutionized hepatocellular carcinoma (HCC) management, necessitating personalized strategies in current guidelines. Despite curat...

GRaph-based analysis for stroke prediction (GRASP): A multi-modal model for identifying first ischemic stroke in high-risk population using UK biobank.

BACKGROUND: Ischemic stroke accounts for 3.71 million deaths annually worldwide. Yet current risk prediction models demonstrate modest discrimination ...

Predicting disease progression in multiple sclerosis with clinically accessible information and technology.

BACKGROUND: Predicting disease progression at the individual level is essential for personalized medicine. We previously developed machine-learning to...

[Exploration and clinical application of the "digital and intelligent surgery" diagnosis and treatment workflow for oral and maxillofacial tumors].

Tumors in the oral and maxillofacial region present significant clinical challenges due to anatomical complexity and high individual variability, with...