Clinical Trials

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 surrounding coastal waters is critical for effective emergency response. To overcome the inherent latency and predictive fidelity limitations of conventional marine dispersion simulations, this study develops an innovative hybrid Physics-Informed Deep Learning...

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 of insufficient adaptability of design-major college students to AI-supported learning environments and examines the factors and mechanisms that influence their adaptability. Through a survey employing a questionnaire, 784 valid responses were gather...

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...

Predicting future cognitive impairment in preclinical Alzheimer's disease using amyloid PET and MRI: A multisite machine learning study.

Predicting the likelihood of developing Alzheimer's disease (AD) dementia in at-risk individuals is important for the design of and optimal recruitmen...

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...

From evolution to rational design: AI-driven engineering of safe and highly efficient food enzymes.

As a representative area of industrial biocatalysis, food enzyme engineering plays a critical role in advancing the food industry. Recently, bioinform...

Current applications of augmented reality in urology: clinical practice, training, and future directions: an EAU endourology and YAU opinion.

PURPOSE OF REVIEW: Augmented reality and related extended-reality technologies have been increasingly investigated in urology to support procedures ch...

Precision functional network imaging-guided transcranial magnetic stimulation: A review of clinical applications through resting-state fMRI.

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique approved for treatment-resistant depression and increasingly appli...

IFCN position statement: use of artificial intelligence in clinical neurophysiology.

In recent years, artificial intelligence (AI) has made significant strides, gaining traction across various domains, including clinical medicine. The ...

Screening of molecular signatures from microRNA and mRNA expression profiling related to the efficacy of the antidepressant duloxetine and analysis of their regulatory relationship.

Previous clinical studies have reported that not all depressed patients respond to antidepressants. Therefore, finding potential predictive molecular ...

The Insomnia EEG Score: a new tool for the classification of people with poor sleep.

Quantitative features could help objectively identify and grade insomnia severity, though there is currently no pathophysiological biomarker of insomn...

Natural bioactive as modulators of airway inflammation and remodeling: mechanistic insights.

Airway diseases such as asthma, COPD, pulmonary fibrosis, and other inflammatory airway conditions remain a significant threat to global health. Tradi...

The nonlinear impact of road safety policy implementation on the severity of road traffic crashes: A fusion of deep learning and Bayesian random parameter methods.

Road crashes remain a primary focus in the field of traffic safety research due to their potentially severe societal and individual consequences. Whil...

Update on pleural mesothelioma.

PURPOSE OF REVIEW: Pleural mesothelioma remains a universally lethal cancer with a rising global burden. This underscores the need for pulmonologists ...

MRI-Guided High-Intensity Focused Ultrasound in Movement Disorders: Targeting Pathologic Brain Circuits With Precision Imaging, From the AJR Special Series on Critical Anatomy.

MRI-guided high-intensity focused ultrasound (MRgHIFU) has emerged as an alternative to other neuromodulatory interventions for patients with medicall...

Fact-Checking Large Language Model Responses to a Health Care Prompt: Comparative Study.

BACKGROUND: Large language models use machine learning to produce natural language. These models have a range of potential applications in health care...

Integrating Next-Generation Sequencing into von Willebrand Disease Diagnostics: Insights from the PCM-EVW-ES Multicenter Project.

Von Willebrand disease (VWD) is the most common inherited bleeding disorder, caused by quantitative or qualitative defects in von Willebrand factor (V...