Hematology

Integrated multi-omics analysis identifies TBC1D10C as an NK- and T cell-associated diagnostic biomarker in childhood obesity.

Childhood obesity is a growing global health crisis associated with an increased risk of metabolic and cardiovascular diseases in adulthood. While accumulating evidence implicates immune dysregulation in obesity pathogenesis, the specific transcriptional alterations of immune cells, particularly NK cells and T cells in the context of childhood obesity, and their potential as non-invasive diagnosti...

Integrating Next-Generation Sequencing into von Willebrand Disease Diagnostics: Insights from the PCM-EVW-ES Multicenter Project.

Von Willebrand disease (VWD) is the most common inherited bleeding disorder, caused by quantitative or qualitative defects in von Willebrand factor (VWF). Diagnosis is challenging and requires integrating bleeding history, VWF antigen and activity measurements, FVIII assays, and specialized phenotyping. Genetic testing is increasingly recognized as a key component. Here, we review current concepts...

Deep learning for pediatric synovial recess distension detection in hemophilia: synthetic image augmentation with styleGAN2-ADA.

PURPOSE: Pediatric musculoskeletal ultrasound (MSKUS) datasets are scarce, especially for rare, sex-linked conditions such as hemophilia. Models train...

Bioinformatics analysis and qRT-PCR validation of iron metabolism-related genes in pediatric asthma.

Pediatric asthma (PA) is a chronic airway disease with a complex etiology, and iron metabolism disorder is believed to be involved in its pathogenesis...

Contextualizing the Patient Blood Management (PBM) Program Through the Lens of Bioethical Principles.

In an increasingly specialized medical landscape, Patient Blood Management (PBM) has emerged as a multidisciplinary and ethically grounded approach to...

Bridging the Gender Gap in Obstructive Sleep Apnea: A Machine Learning Approach to Screening Women for Moderate-to-Severe Disease.

INTRODUCTION: Obstructive sleep apnea (OSA) can cause severe complications if left untreated. Several challenges hinder OSA identification in females,...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...

Hi-Compass: a depth-aware deep learning framework for predicting cell-type-specific 3D genome organization from single-cell to spatial resolution.

Three-dimensional genome organization controls cell-type-specific gene expression through chromatin interactions, yet systematic analysis across diver...

Neutrophil CD14 is a driver and a therapeutic target for deep vein thrombosis.

Neutrophil-mediated persistent inflammation and neutrophil extracellular trap formation (NETosis) are critical in the pathogenesis of deep vein thromb...

AI-based autism identification from hyperspectral imaging detection of oxidative stress in pediatric red blood cells.

BACKGROUND: Oxidative stress (OS) plays a key role in many pathologies, yet the non-invasive, label-free, and cost-effective detection remains a chall...

Artificial intelligence reshaping the paradigm of hematologic malignancy diagnosis and treatment: From static assessment to dynamic precision management.

Cardiovascular toxicity of ethyl maltol exposure: a comprehensive investigation from virtual screening to experimental validation.

Ethyl maltol is a ubiquitous synthetic flavor enhancer. Despite its widespread use in foods, beverages, and electronic cigarettes, and its potential f...

An interpretable machine learning tool for rheumatoid arthritis screening: integrating novel cellular morphological parameters with routine blood count indices.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease that can cause significant disability. Early detection is vital for improving ou...

In-hospital outcomes and cost-effectiveness of transcatheter aortic valve replacement among younger patients: a double/debiased machine learning approach using electronic health records in Germany.

BACKGROUND: The prevalence of severe symptomatic aortic stenosis is increasing with population aging. Although surgical aortic valve replacement (SAVR...

Development of a Predictive Model for the Latency Period in Preterm Premature Rupture of Membranes Before 32 Weeks' Gestation.

BACKGROUND: Only 13.7% of corticosteroid treatments occurred within the most effective treatment time window for preterm premature rupture of membrane...

Bridging Trials and Real Life in Fixed-Duration BTKi-Venetoclax for CLL: A Delphi-Enhanced Synthesis Incorporating Artificial Intelligence (AI) Benchmarks.

BACKGROUND: Optimal patient selection for the most effective BTK inhibitor (BTKi) partner of venetoclax in fixed-duration (FD) BTKi-venetoclax regimen...

Identification of a novel platelet-related prognostic model for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly lethal malignancy with high invasiveness and metastasis. Despite progress in its treatment, the high mortal...

Towards transparent and interpretable screening: multi-biofluid FTIR spectroscopy with LLM-Augmented explainability for pancreatic cancer detection.

Early detection of pancreatic cancer remains a critical challenge in oncology, with current diagnostic methods often failing to identify the disease u...

Deep learning-driven quantitative spectroscopic photoacoustic imaging for segmentation and oxygen saturation estimation.

Spectroscopic photoacoustic (sPA) imaging can potentially estimate blood oxygenation saturation (sO2) in vivo noninvasively. However, quantitatively a...

Evaluating AI in leukocyte classification: performance of the AI system against 15 morphology experts.

Artificial intelligence (AI)-based digital morphology analyzers are vital for clinical hematology but face critical challenges in identifying immature...