Latest AI and machine learning research in covid-19 for healthcare professionals.
We aimed to develop and validate a predictive model combining radiomics, deep learning, and clinical features for the preoperative prediction of the short-term efficacy of initial drug-eluting bead transarterial chemoembolization (DEB-TACE) treatment in patients with hepatocellular carcinoma (HCC). This retrospective cohort study included 113 internal and 32 external patients from three centers wi...
Minimal/measurable residual disease (MRD) analysis using multiparametric flow cytometry (MFC-MRD) is essential for therapy stratification in acute leukemia; however, conventional analysis is limited by analyst-dependent variability and complex manual gating. Although machine learning approaches have been proposed, their clinical implementation requires large reference datasets and standardized ant...
PURPOSE: Lumbar spinal stenosis (LSS) is a common degenerative spinal condition and a leading cause of pain and disability in adults. With increasing ...
BACKGROUND: Hyperlipidemia is a major modifiable contributor to atherosclerotic cardiovascular disease (ASCVD). Despite statins as first-line therapy,...
Artificial intelligence has accelerated epitope and antigen discovery, but prediction alone cannot determine vaccine readiness. Translational design r...
BACKGROUND: Biomedical informatics increasingly reuses clinical artificial intelligence (AI) benchmarks, yet successor releases are often treated as i...
PURPOSE: The purpose of this study was to compare, across readers with varying experience, the characterisation of prostate MRI lesions as grade group...
INTRODUCTION: Differentiating the nonfluent/agrammatic and logopenic variants of primary progressive aphasia (PPA; nfvPPA and lvPPA, respectively) rem...
PURPOSE: Deep learning-based three-dimensional (3D) dose prediction is widely used in automated radiotherapy workflows. However, most existing models ...
BACKGROUND: Antibody-mediated rejection (AMR) is the main driver of late kidney allograft loss. Anti-HLA donor-specific antibodies (DSA) are strongly ...
BACKGROUND: Abstracts and Discussion sections serve distinct functions: Abstracts are optimized for brevity and impact, while Discussion sections cont...
BACKGROUND: Polygenic risk scores for Alzheimer's disease (AD-PRS) are widely used to estimate genetic susceptibility to AD, but their relationship wi...
BACKGROUND: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide. Accurate early prediction of response ...
Antibodies targeting small molecules play indispensable roles in food safety, environmental monitoring, clinical diagnostics, and immunotherapy. The g...
The COVID-19 pandemic has caused substantial worldwide disruptions in health, economy, and society, manifesting symptoms such as loss of smell (anosmi...
Oxidation of tryptophan (Trp) residues in therapeutic antibody complementarity-determining regions (CDRs) can impair binding affinity, stability, and ...
Human surgery and autopsy specimens are routinely stored as formalin-fixed paraffin-embedded (FFPE) tissue blocks for decades, creating vast archives ...
BACKGROUND: Colorectal cancer (CRC) is a major global health burden. While immune checkpoint inhibitors have greatly advanced cancer therapy, their th...
INTRODUCTION: Hereditary transthyretin amyloidosis (ATTRv) is a rare progressive, potentially life-threatening multisystem disorder caused by mutation...
Machine learning (ML) models integrating genetic and clinical data show promise for personalizing antiplatelet therapy after myocardial infarction (MI...