Latest AI and machine learning research in medicare for healthcare professionals.
BACKGROUND: Clinical trials are essential for advancing cancer care, but identifying eligible patients in surgical clinics can be challenging due to the manual and time-consuming enrollment process. Artificial intelligence tools, such as large language models, have the potential to automate aspects of clinical trial matching. This study identified reasons why patients did not enroll in a clinical ...
Atomically thin two-dimensional (2D) ceramics, such as monolayer hexagonal boron nitride (h-BN), present potential for disruptive advances in separations. However, sub-atomic scale separation of hydrogen isotopes (H+/D+) require near pristine 2D material membranes, and scalable synthesis of such high-quality h-BN comparable to mechanically exfoliated crystals remains a significant challenge. Here,...
BACKGROUND: Falls and related injuries (FRI) pose a large burden among older adults with depression. Proactively identifying individuals at high FRI r...
Electrochemical CO2 reduction to single-carbon products is central to sustainable fuels and chemicals, but under industrially relevant conditions elev...
Hearing loss affects approximately two thirds of adults in the United States aged 70 years or older and frequently remains untreated despite its well-...
PURPOSE: In online cone beam computed tomography (CBCT)-based adaptive radiation therapy (ART), nodal recontouring ensures sufficient nodal coverage b...
Exome sequencing (ES) has transformed genomic research and clinical diagnostics by enabling precise identification of disease-associated variants with...
Mycelial biocomposites are sustainable alternatives to nonbiodegradable materials in building and packaging. Efficient manufacturing requires accurate...
PURPOSE: AlphaMissense is a newer deep learning-based variant predictor that evaluates the structural consequences of missense variants, the most comm...
BACKGROUND: Predicting mortality in chronic obstructive pulmonary disease (COPD) patients supports clinical decision-making and resource allocation. W...
BACKGROUND AND OBJECTIVE: Artificial Intelligence (AI) models for electrocardiogram (ECG) interpretation rely on large, diverse datasets, but existing...
BACKGROUND: Identifying the brand of reverse shoulder arthroplasty (rTSA) implanted is key in the postoperative evaluation of patients, a process that...
BACKGROUND: Many medications are associated with long QTc. Current long QTc predictors have limited generalizability and/or modest performance. OBJECT...
Coronary artery disease (CAD) remains a leading driver of cardiovascular mortality, requiring diagnostic systems that deliver high discrimination, sta...
Hospital-acquired pneumonia (HAP) remains the most frequent and lethal hospital acquired infection, driving ICU mortality, prolonged length of stay, a...
Comorbid anxiety disorders are common among patients with major depressive disorder (MDD), but their impact on outcomes of digital and smartphone-deli...
BACKGROUND: Electroencephalogram (EEG) microstates reflect momentary localized brain activity and may indicate spontaneous fluctuations within large-s...
BACKGROUND: Clinical trials face unprecedented challenges including recruitment delays affecting 80% of studies, escalating costs exceeding $200 billi...
Grief is a complex and multifaceted process. While there is no reason to think that the grieving process would be dissimilar if an LGBTQ+ individual l...
Deep incremental hashing can generate hash codes incrementally for new classes, while keeping the existing ones unchanged. Existing methods typically ...