Clinical Trials

Uncertainty-aware probabilistic graph neural networks for road-level traffic crash prediction.

Traffic crashes present substantial challenges to human safety and socio-economic development in urban areas. Developing a reliable and responsible traffic crash prediction model is crucial to address growing public safety concerns and improve the safety of urban mobility systems. Traditional methods face limitations at fine spatiotemporal scales due to the sporadic nature of high-risk crashes and...

Efficacy of automated machine learning models and feature engineering for diagnosis of equivocal appendicitis using clinical and computed tomography findings.

This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with automated feature engineering and selection (autofeat), focusing on clinical manifestations, and a model integrating both clinical manifestations and CT findings in adult patients with ambiguous computed tomography (CT) results for acute appendicitis (AA). This evaluation was compared with conventional sing...

Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.

Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but addressing heterogeneity in...

Restoring of Interhemispheric Symmetry in Patients With Stroke Following Bilateral or Unilateral Robot-Assisted Upper-Limb Rehabilitation: A Pilot Randomized Controlled Trial.

Bilateral robotic rehabilitation has proven helpful in the recovery of upper limb motor function in patients with stroke, but its effects on the corti...

Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.

OBJECTIVES: The paper develops a machine learning-based safety index for classifying traffic conflicts that can be used to estimate the frequency of s...

The Impact of Medical Explainable Artificial Intelligence on Nurses' Innovation Behaviour: A Structural Equation Modelling Approach.

This study aims to investigate the influence of medical explainable artificial intelligence (XAI) on the innovation behaviour of nurses, as well as e...

Randomized controlled trial of an artificial intelligence diagnostic system for the detection of esophageal squamous cell carcinoma in clinical practice.

BACKGROUND: Artificial intelligence (AI) has made remarkable progress in image recognition using deep learning systems. It has been used to detect eso...

How can quantum computing be applied in clinical trial design and optimization?

Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success ...

Effects of high-definition tDCS targeting individual motor hotspot with EMG-driven robotic hand training on upper extremity motor function: a pilot randomized controlled trial.

BACKGROUND: Delivering HD-tDCS on individual motor hotspot with optimal electric fields could overcome challenges of stroke heterogeneity, potentially...

Machine learning approaches to evaluate heterogeneous treatment effects in randomized controlled trials: a scoping review.

BACKGROUND AND OBJECTIVES: Estimating heterogeneous treatment effects (HTEs) in randomized controlled trials (RCTs) has received substantial attention...

Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo.

OBJECTIVE: Predicting an individual's response to antidepressant medication remains one of the most challenging tasks in the treatment of major depres...

Sensory Stimulation and Robot-Assisted Arm Training After Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Functional recovery after stroke is often limited, despite various treatment methods such as robot-assisted therapy. Repetitiv...

Enhancing trainee performance in obstetric ultrasound through an artificial intelligence system: randomized controlled trial.

OBJECTIVE: Performing obstetric ultrasound scans is challenging for inexperienced operators; therefore, the prenatal screening artificial intelligence...

SafeRPlan: Safe deep reinforcement learning for intraoperative planning of pedicle screw placement.

Spinal fusion surgery requires highly accurate implantation of pedicle screw implants, which must be conducted in critical proximity to vital structur...

Main challenges on the curation of large scale datasets for pancreas segmentation using deep learning in multi-phase CT scans: Focus on cardinality, manual refinement, and annotation quality.

Accurate segmentation of the pancreas in computed tomography (CT) holds paramount importance in diagnostics, surgical planning, and interventions. Rec...

Engagement analysis of a persuasive-design-optimized eHealth intervention through machine learning.

The challenge of sustaining user engagement in eHealth interventions is a pressing issue with significant implications for the effectiveness of these ...

Progress of machine learning-based biosensors for the monitoring of food safety: A review.

Rapid urbanization and growing food demand caused people to be concerned about food safety. Biosensors have gained considerable attention for assessin...

The effect of artificial intelligence supported case analysis on nursing students' case management performance and satisfaction: A randomized controlled trial.

BACKGROUND: Rapid developments in artificial intelligence have begun to necessitate changes and transformations in nursing education.

Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank.

The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Her...

Beneficial effects of cranberry juice enriched with omega-3 fatty acids in patients with type 2 diabetic and periodontal disease: A randomized pilot clinical trial.

BACKGROUND: The present study evaluated the effects of cranberry juice enriched with omega-3 on inflammatory, oxidative stress, and periodontal status...