COVID-19

Comparative Evaluation of Deep Learning Models for 3D Segmentation and Volumetry of Vestibular Schwannomas Using Large Heterogeneous Data Sets with External Validation.

BACKGROUND AND PURPOSE: 3D segmentation and volumetry of vestibular schwannomas (VSs) is a more accurate method to determine tumor growth on serial imaging, but manual annotation is time-consuming to implement in routine clinical practice. We evaluated and compared 5 deep learning-based segmentation models (nnUNet [Base, ResEncL], U-Mamba, UNETR, and MedSAM) for 3D VS segmentation and volumetry, a...

Classifying Post-COVID "Brain Fog" Patients and Identifying Key ROIs via Graph Neural Network Model.

Brain fog has raised significant public health concerns as a common neurocognitive impairment in the post-COVID-19 condition, involving memory loss, poor concentration, and language difficulties. However, their neural mechanisms remain unclear, and objective resting-state fMRI-based diagnostic tools are still lacking. To address these challenges, we first recruited 72 patients who experienced pers...

In silico discovery of nanobody binders to a G-protein coupled receptor using AlphaFold-Multimer.

Antibodies are central mediators of the adaptive immune response, and they are powerful research tools and therapeutics. Antibody discovery requires s...

SHAP-based interpretable machine learning with longitudinal delta-radiomics across seven weeks of treatment for xerostomia prediction in head-and-neck cancer.

Association of epigenetic trajectory with development of clinical rheumatoid arthritis in anti-citrullinated protein antibody positive individuals: Targeting Immune Responses for Prevention of Rheumatoid Arthritis (TIP-RA).

OBJECTIVE: The presence of anti-citrullinated protein antibodies (ACPAs) in the absence of clinical inflammatory arthritis (IA) identifies individuals...

Comprehensive RNA-binding protein analyses and deep learning uncover genetic constraints and disease associations in protein-RNA interfaces.

RNA-binding proteins (RBPs) orchestrate post-transcriptional processes, including splicing, cleavage and polyadenylation, and translation. Our updated...

The adaptive immune receptors in a big data world.

Antibodies and T cell receptors are the molecular basis of immune memory, and have become the foundation for generations of clinically successful biol...

Development and Validation of a Deep Learning-Based Segmentation Method for Fenestration Marker and Graft Body Identification in Fenestrated Endovascular Aortic Repair.

OBJECTIVE: To develop and validate a deep learning-based segmentation method for accurate identification of fenestration markers and graft body contou...

A deep dive into ferritin nanoparticle advancements: experimental and computational perspectives.

Ferritin, a natural iron-storage protein, has emerged as a versatile platform in nanotechnology and biomedicine due to its biocompatible 12 nm nanocag...

Deep Learning and Experimental Validation of BRCA1-Associated Protein-1 Missense Variant Pathogenicity in Uveal Melanoma.

OBJECTIVE: To benchmark the pathogenicity predictions of AlphaMissense, a deep learning model, against high-throughput functional scores from saturati...

FDA-authorized oncology artificial intelligence and machine learning devices and their clinical evidence: A cross-sectional analysis.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) tools are increasingly embedded in cancer care, yet the scope of U.S. Food and Drug...

Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in chronic spontaneous urticaria and autophagy based on machine learning.

BACKGROUND: The exact molecular mechanisms governing a heightened risk of chronic spontaneous urticaria (CSU) associated with autophagy remain largely...

Early prediction of gestational diabetes mellitus with clinical characteristics, cell-free DNA and genetic variants.

BACKGROUND: Gestational diabetes mellitus (GDM) remains a prevalent and heterogeneous pregnancy complication with limited strategies for early identif...

Prevalence of Lipoprotein(a) Testing in Patients With Atherosclerotic Cardiovascular Disease Within a Large Australian Cardiology Network.

BACKGROUND: Increased lipoprotein(a) (Lp[a]) is a genetically determined causal risk factor for atherosclerotic cardiovascular disease (ASCVD). Histor...

Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.

AIMS/HYPOTHESIS: Clinically actionable biomarkers that accurately reflect the health status of the beta cell are needed to improve risk stratification...

Isolated Nausea and Pretibial Rash in a Returning Traveler: Forme Fruste of Leptospirosis.

Leptospirosis is difficult to diagnose because of protean nonspecific clinical manifestations and the lack of rapid, actionable laboratory testing. A ...

Serum-antibody Profiling of H3N2-infected Ferrets Using a Combinatorial Phage-display Random Peptide Library.

The repertoire of antibodies in serum, known as the "IgOme", is highly diverse and unique to each individual as it reflects the cumulative history of ...

Multi-Crop Sclerotinia sclerotiorum Apothecia Prediction Models for Irrigated Environments are Improved by On-Site Weather Monitoring and Supervised Machine Learning.

Sclerotinia sclerotiorum causes Sclerotinia stem rot, or white mold, on multiple economically important crops in Michigan. Soybean farmers and crop co...

Identification and Experimental Validation of Biomarkers Associated with PI3K/AKT Signaling Pathway in Spinal Cord Injury.

Spinal cord injury (SCI) refers to trauma to the spinal cord resulting in functional deficits. Dysregulation of the phosphoinositide 3-kinase/serine-t...

Mortality Prediction Among People Living With HIV on Antiretroviral Therapy in Public Health Facilities in Gondar City Administration, Northwest Ethiopia: Machine Learning-Based Study.

BACKGROUND: Predicting mortality among people living with HIV enables clinicians to implement timely, targeted, and preventive interventions at the st...