Latest AI and machine learning research in us health policy for healthcare professionals.
BACKGROUND: Interictal epileptiform discharges (IEDs) are transient spikes or waves that occur in electroencephalography (EEG) records and can help support the diagnosis and classification of epilepsy. High-throughput machine learning models aim to automate the detection of IEDs. Previous evaluations of machine learning models have reported non-inferiority compared to human experts, but these stud...
BACKGROUND: The current gold standard for the diagnosis of coronary artery disease (CAD) is invasive angiography; however, it is an invasive procedure. Therefore, we developed an artificial intelligence model designed to predict significant CAD from a resting digital 12-lead electrocardiogram (ECG). OBJECTIVES: This retrospective study assessed the model's ability to predict clinically significant...
Global population aging and increased chronic stress due to numerous mass disasters including those related to pandemics, climate change, war, displac...
BACKGROUND: Predicting health insurance uptake remains a critical challenge for policymakers and insurance providers seeking to optimise coverage stra...
INTRODUCTION: The COVID-19 pandemic has intensified global health challenges, including a silent but escalating crisis: multidrug-resistant organisms ...
BACKGROUND: The triglyceride-glucose index (TyG) and atherogenic index of plasma (AIP) are emerging metabolic biomarkers associated with cardiovascula...
Artificial intelligence (AI) is poised to play a transformative role in pandemic preparedness, with the potential to enhance surveillance, risk assess...
BACKGROUND AND STUDY AIMS: Polypectomy-related costs could potentially be reduced through optical diagnosis strategies, such as 'diagnose-and-leave' a...
BACKGROUND: Endometrial carcinoma (UCEC) exhibits a rising incidence in China, imposing a substantial burden on both women and society. Identifying bi...
Histopathological hematoxylin and eosin (H&E) slides contain valuable prognostic information for pancreatic ductal adenocarcinoma (PDAC), yet systemat...
BACKGROUND: This study tests the hypothesis that postoperative undertriage of high-acuity patients to hospital floor units is associated with new post...
BACKGROUND.—: Cardiovascular risk estimation for life insurance underwriting relies on risk estimation from conventional metrics: age, sex, smoking st...
The role of adipose tissue in predicting microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) remains unclear. This study prop...
OBJECTIVES: Leg dystonia in cerebral palsy (CP) is debilitating but remains underdiagnosed. Routine clinical evaluation has only 12% accuracy for leg ...
PURPOSE: Biocompatible collagen membranes (CM) are widely used in regenerative dentistry, particularly in guided tissue regeneration (GTR) and guided ...
BACKGROUND AND HYPOTHESIS: Digital remote monitoring (DRM) captures service users' health-related data remotely using devices such as smartphones and ...
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are used as an evaluation method in medical education, but require significant pedagogi...
Artificial intelligence and machine learning (AI/ML) in prevention science may improve or perpetuate health inequities. Community engagement is one pr...
We aim to present recent advancements in predictive markers for lymphomagenesis in SjD, concisely organize existing knowledge, and identify correspond...
BACKGROUND: Accurate assessment of 90-day functional outcomes after anterior circulation large vessel occlusion (LVO) stroke remains challenging. Conv...