Clinical Trials

Machine learning-based ground motion simulation for seismic hazard assessment of critical water infrastructure in Azerbaijan (Case study: Major Shamkir water reservoir).

This study focuses on simulating ground motion for the Shamkir Water Reservoir area in Azerbaijan using machine learning algorithms to enhance regional seismic hazard assessments. Given the reservoir's location in a seismically active zone, potential earthquake-induced impacts on dam infrastructure pose critical safety concerns. A synthetic ground motion database comprising 3,013 records was devel...

Artificial intelligence in gastroenterology clinical practice: Scoping review of large language model applications.

BACKGROUND: Advances in artificial intelligence have brought renewed attention to tools that can work with the large amount of written information generated in clinical practice. Among these, large language models (LLMs) stand out for their ability to interpret and generate medical text in a flexible, context-aware way. Gastroenterology, like many specialties, produces a wide range of narrative an...

Artificial intelligence for adaptive neuromodulation in drug-resistant epilepsy.

Drug-resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortalit...

Safeguarding Online Research in Eating Disorders Against Fraud: Increasing Risks and Practical Recommendations.

OBJECTIVE: Recent growth of online research has been accompanied by an increase in reports of fraudulent participants, which can significantly compris...

Designing a Carbohydrate Counting App for Young Adults With Type 1 Diabetes: Usability Testing Interview Study.

BACKGROUND: Carbohydrate counting (CC) assists people with type 1 diabetes (T1D) adjust mealtime insulin doses; however, it is often burdensome. Mobil...

A concept-enhanced, knowledge graph-guided framework for interpretable PCOS prediction: a case study in explainable biomedical artificial intelligence.

CONTEXT: Overcoming the disconnect between efficient Machine Learning (ML) techniques and its therapeutic applicability necessitates frameworks that p...

The future of digital innovation in transforming food safety systems in the developing world.

Low- and middle-income countries bear the most significant burden of foodborne diseases, impacting their food and nutrition security, trade, and ultim...

Machine learning assisted differentiation of low acuity patients at dispatch: The MADLAD randomized controlled trial.

BACKGROUND: Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more patients requiring an ambulance than ther...

AI-assisted videolaryngoscopy improves intubation success: results from a randomized simulation trial.

Video laryngoscopy has become an integral part of today's airway management. Despite its advantages, loss of depth perception and increased cognitive ...

Viewpoint on the Consequences and Mitigation of Cognitive Bias in the Radiological Interpretation of Breast Cancer Imaging Using Artificial Intelligence.

Artificial intelligence (AI) is increasingly integrated into breast imaging workflows, offering the potential to enhance diagnostic accuracy, efficien...

Using U-Nets to Predict the Effects of Head Motion on Simulated Specific Absorption Rate for Ultra-High Field Magnetic Resonance Imaging With Parallel Transmission.

PURPOSE: Ultrahigh-field MRI requires careful management of the specific absorption rate (SAR), which is subject and subject-position dependent. Withi...

Interpretable spatiotemporal traffic crash risk prediction using DMD-based graph neural networks.

Spatiotemporal prediction of urban traffic crashes is an important basis for proactive safety management, yet many existing models have difficulty cap...

Practical Integration of Bedside Real-Time Lung Ultrasound and Electrical Impedance Tomography for Guiding Personalized Perioperative Lung Protective Ventilation in Cardiothoracic and Vascular Anesthesia.

Patients undergoing cardiothoracic and vascular surgery are at uniquely high risk for postoperative pulmonary complications due to the confluence of s...

Evaluating the effects of adjunct VR-haptic simulator practice in preclinical restorative training and predicting student performance using machine learning: a randomized controlled trial.

Measuring Accuracy (Classification Probabilities, Positive, and Negative Predictive Values) of Executive Function Electroencephalogram Metrics in Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for and Perspectives From the SINCRONIA Study.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder worldwide, affecting approximately 5%-7%...

Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography.

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome rather than a single disease. Patients who meet the same diagnostic cr...

Effectiveness of Thoracic Paravertebral Block in Minimally Invasive Vertebroplasty: A Retrospective Cohort Study Focusing on Pain Trajectories and Sagittal Spinal Alignment.

PURPOSE: To evaluate the effectiveness of ultrasound-guided thoracic paravertebral block (TPVB) combined with general anesthesia (GA) versus GA alone ...

Large language models enhance diagnostic reasoning of medical students in rheumatology: a randomized controlled trial.

Robot-Assisted Therapy for Upper Limb Rehabilitation After Stroke: Umbrella Review.

BACKGROUND: Stroke is a leading cause of long-term upper limb disability, severely impacting patients' independence and quality of life. Robot-assiste...

Long-term outcomes of lateral sinus floor elevation: A machine-learning analysis, systematic review, and meta-analysis of predictive factors.

OBJECTIVES: To quantify long-term (≥ 5 years) implant survival after lateral sinus floor elevation (LSFE) and to identify clinical predictors of long-...