Hematology

CAR T-cells in hematologic malignancies: Advances, challenges, and future directions.

Chimeric antigen receptor (CAR) T-cell therapy has transformed the management of hematologic maligna...

Expectations and Limitations of Artificial Intelligence in Blood Cancer Diagnosis.

In this commentary, we open the debate on what can be expected from artificial intelligence (AI) in ...

Maternal Gut Microbiome as a Predictor of Insulin Therapy Requirement in Gestational Diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) often requires pharmacological intervention beyond l...

Comparison of the diagnostic performance of machine learning algorithms for differentiating iron deficiency anemia and thalassemia.

Machine learning-based multiclass model for autoimmune disease diagnosis and classification through nailfold videocapillaroscopy features.

OBJECTIVE: To develop and validate a predictive model for distinguishing controls (Ctr), rheumatoid ...

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.

Explainable machine learning with routine biomarkers identifies culture-defined bacteremic urosepsis.

Urosepsis is a severe complication of urinary tract infection (UTI) and may lead to organ dysfunctio...

Cell-free chromatin state tracing reveals disease origin and therapy responses.

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both health...

Determinants of labor epidural analgesia uptake and associations with maternal-neonatal outcomes: a stratified cohort study with risk prediction modeling.

BACKGROUND: Labor pain is a major physiological and psychological stressor for women during childbir...

Plasma proteomic profiles of lung volume-based phenotypes in Tobacco-Exposed Individuals Without Spirometric COPD.

BACKGROUND: Among individuals with a history of smoking but preserved spirometry (tobacco exposed wi...

A Multiomic Liquid Biopsy for the Earlier Detection of Colorectal Cancer.

UNLABELLED: Timely diagnosis and intervention in colorectal cancer are critical to improving patient...

An optimized machine learning model based on hematological indicators for the noninvasive identification of baicalin's therapeutic effects in pulmonary hypertension.

Pulmonary hypertension (PH) is a progressive cardiopulmonary disorder with high mortality, necessita...

Early recurrence prediction and risk stratification of hepatocellular carcinoma after transarterial chemoembolization achieving imaging complete response based on contrast-enhanced CT machine learning.

OBJECTIVES: To develop and validate machine learning (ML) models using clinical and contrast-enhance...

Integrated CTC Enrichment and Dual-Responsive Nanoprobe Identification Enable Intelligent Liquid Biopsy-Based Cancer Diagnosis.

This work addresses the challenge of accurately identifying living circulating tumor cell (CTC) from...

TCR sequencing in cancer immunology and immunotherapy: what, when, where, why, and how.

T-cell receptors (TCRs) are generated through somatic recombination of variable (V), diversity (D), ...

Proteomics-based machine learning model for predicting secondary infection in HBV-related liver failure.

Patients with Hepatitis B Virus-related liver failure are highly vulnerable to secondary infections ...

Pharmacological stabilization of hypoxia-inducible factor 1-α dampens the interferon response and promotes glycolysis in Aicardi-Goutières syndrome.

Aicardi-Goutières syndrome (AGS) is a genetic type I interferon (IFN)-mediated disease characterized...

Circulating tumor cells (CTCs) enumeration and machine-learning based diagnostic biomarkers for breast cancer detection.

BACKGROUND: Circulating tumor cells (CTCs) are detectable in early-stage cancer and may enable early...

Predicting short-term mortality in severe cirrhosis: An interpretable machine learning model integrating routine clinical indicators.

BACKGROUND: The critical need for precise risk stratification in severe liver cirrhosis is underscor...

Rapid Diagnosis of Bacteremia in Febrile Pediatric Oncology Patients via Host-Response Infrared Spectroscopy of Blood and Machine Learning.

Bacteremia is a life-threatening complication and a leading cause of sepsis and septic shock in pati...

M[Formula: see text]DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson's disease(PD) progression using whole-blood RNA sequencing data.

With emerging single-cell transcriptomics data, deep learning approaches have enabled the diagnosis ...