Hematology

BRPtools: An AutoML-Powered web platform for multiclass disease prediction from bulk blood RNA-seq data.

Blood-based transcriptomic profiling provides a minimally invasive approach for disease diagnosis; however, the integration of large-scale, heterogeneous RNA sequencing (RNA-seq) datasets remains challenging. Here, we manually curated and uniformly reprocessed 134 publicly available human RNA-seq datasets (n = 9,872 samples), covering 88 distinct blood-related diseases from whole blood and periphe...

[Position paper of the German Society of Cardiology-quality criteria for performing catheter ablation of atrial fibrillation: executive summary].

The updated German Society of Cardiology (DGK) position paper on catheter ablation of atrial fibrillation (AF) [1] presents the current evidence, techniques, and quality standards, which have evolved significantly since 2017 alongside indications, technology, and the role of ablation in therapy. Pulmonary vein isolation (PVI) remains the cornerstone of AF ablation. In addition to established proce...

Application of an AI-Based Pediatric Early Warning Score in the Pediatric Emergency Department: Cross-Sectional Study.

BACKGROUND: Pediatric emergency departments see a high volume of patients. Given that children often cannot describe their condition and there is a sh...

Feasibility study of non-invasive blood pressure measurement based on multidimensional characteristics of radial artery pressure pulse wave.

OBJECTIVE: This study focuses on a non-invasive blood pressure prediction method based on radial artery pulse wave feature analysis, aiming to achieve...

Using clinical and thrombus characteristics to predict the etiology of ischemic stroke: An analysis of the INSIGHT registry.

BACKGROUND AND PURPOSE: Ischemic stroke comprises about 87% of all stroke cases in the US. 20% of these have a cardioembolic (CE) etiology, and 25% ar...

The Role of Inflammatory Biomarkers in Disease Severity and Treatment Response across Psoriasis, Atopic Dermatitis, and Hidradenitis Suppurativa-A Narrative Review.

Chronic inflammatory skin diseases (CISDs) such as psoriasis (PsO), atopic dermatitis (AD), and hidradenitis suppurativa (HS) involve both cutaneous a...

CT-based 3D planning-supported stem-free screw-cement augmentation versus 2D radiograph-planned short-stem reconstruction for AORI type I-II medial tibial defects in TKA: a two-year retrospective study.

BACKGROUND: Medial tibial defects in varus knee osteoarthritis (KOA) challenge alignment and tibial support in primary total knee arthroplasty (TKA). ...

Leveraging Machine Learning and Network Biology Approaches to Predict Brain Gene Expression from Blood Transcriptomes.

Blood-based biomarkers offer a promising non-invasive strategy for detecting disease-related changes and monitoring tissue and organ health, including...

Correspondence on 'Evaluation of the impact of NOAC underdosing and exploration of bleeding risk factors in elderly patients with atrial fibrillation: artificial intelligence-based approach' by Protzenko et al.

Machine-Learning-Based Predictive Model for Trifecta Achievement in Robot-Assisted Partial Nephrectomy.

OBJECTIVE: To develop and internally validate a machine-learning-based nomogram for predicting trifecta achievement in patients undergoing robot-assis...

Prediction Model for Delirium in Patients with Sepsis-Associated Liver Injury: An Interpretable Machine Learning Approach.

BackgroundPatients with sepsis-associated liver injury (SALI) are at marked risk of delirium, a severe complication strongly linked with poor neurolog...

Dual-Scale StaphAIR: Predictive Modeling for the Diagnosis of S. aureus Infection via Simultaneous Detection and Quantification of Cytokines and Antibodies.

Staphylococcus aureus causes life-threatening bacterial infections. Current diagnostics for bone infection consist of invasive sample collection and l...

Whole genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis.

BACKGROUND: Endometriosis, despite its high prevalence, is underdiagnosed and poorly managed due to lack of clinically validated biomarkers and pathop...

A hybrid machine learning approach for automated malaria diagnosis from thin blood smear images.

BACKGROUND: Malaria remains a significant global health challenge, requiring diagnostic approaches that are rapid, cost-effective, and accurate. The p...

Integrated Diagnosis of Submassive Pulmonary Embolism Using Computed Tomography Angiography, Echocardiography, and Artificial Intelligence.

OBJECTIVES: Early intervention in submassive pulmonary embolism (SMPE) has been shown to improve long-term cardiopulmonary outcomes compared to antico...

Interpretable machine learning using accumulated local effects to characterise predictors of subclinical leaflet thrombosis after self-expanding transcatheter aortic valve implantation.

OBJECTIVES: Subclinical leaflet thrombosis is an early form of bioprosthetic valve dysfunction after transcatheter aortic valve implantation. Predicti...

TIME: A Taylor-Inspired Mixed-Effects Model for IDH Prediction.

BACKGROUND: Intradialytic hypotension (IDH) is a critical complication in hemodialysis that increases morbidity and treatment risks, yet existing mach...

Complication Risk Classification in Children and Adolescents With Type 1 Diabetes: Interpretable Machine Learning Study Based on Saudi Clinical Guidelines.

BACKGROUND: Complication risks in children and adolescents with type 1 diabetes (T1D) can lead to serious health outcomes if not detected early. Despi...

Multicentric data challenge for artificial intelligence-based classification of leukocytes: results from the CytologIA consortium.

Accurate morphological classification of blood leukocytes remains a cornerstone of hematological diagnostics but still relies on manual expertise, lea...

Standardization of surgical gesture taxonomy: a SAGES Delphi consensus study.

INTRODUCTION: Artificial intelligence (AI) for surgical workflow analysis often fails to generalize because surgical actions lack a standardized, fine...