Hematology

Thrombopoietin receptor agonists in immune thrombocytopenia: a comparative review of mechanisms, efficacy, and the future of personalized management.

INTRODUCTION: Thrombopoietin receptor agonists (TPO-RAs) have reshaped the management of chronic immune thrombocytopenia (ITP) by directly targeting impaired platelet production, a mechanism previously overshadowed by immune-mediated destruction. The three approved agents - romiplostim, eltrombopag, and avatrombopag - all stimulate the c-Mpl receptor but differ in their molecular interactions, pha...

Using artificial intelligence to predict sexual health outcomes in endometriosis: a decision tree model algorithm.

BACKGROUND: Endometriosis profoundly impairs sexual function through complex interactions between pain, hormonal disturbances, psychological distress, and sociodemographic factors. AIM: To develop and validate a decision tree-based model identifying key predictors of sexual dysfunction in women with endometriosis. METHODS: We conducted a cross-sectional online survey among 1586 women with endometr...

An interpretable machine learning model for early risk stratification of medium-to-giant coronary artery aneurysm in Kawasaki disease: development and external validation.

BACKGROUND: Medium-to-giant coronary artery aneurysm (MGCAA) represents the most severe complication of Kawasaki disease (KD) and remains difficult to...

Artificial intelligence in transfusion medicine: Soon the end of the beginning?

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

Artificial Intelligence Applications in COVID-19-Associated Coagulopathy: Lessons Learned.

Coronavirus disease 2019 (COVID-19)-associated coagulopathy (CAC) is a thromboinflammatory syndrome marked by endothelial injury, micro- and macrovasc...

Early prediction of adult lymphoma-associated haemophagocytic lymphohistiocytosis using an interpretable machine learning model.

Lymphoma-associated haemophagocytic lymphohistiocytosis (LA-HLH) is associated with a high mortality rate, making early diagnosis and appropriate trea...

Fundamentals of big data and artificial intelligence in transfusion medicine.

Within the digital transformation of medicine, transfusion medicine has quietly become a big-data discipline. The long-standing tradition of blood pro...

Harnessing big data and artificial intelligence in transfusion medicine: Opportunities for precision, safety and efficiency.

Transfusion medicine generates enormous volumes of data across the vein-to-vein continuum, spanning donor characteristics, laboratory testing, compone...

Integrated bioinformatics and machine learning, research on specific biomarkers for large-artery atherosclerosis stroke.

Large-artery atherosclerosis stroke (LAA) is the main subtype of ischemic stroke. Currently, the diagnosis of LAA is confirmed through magnetic resona...

A dual-modal machine learning framework integrating red blood indices and smartphone-captured microscopic images for β-thalassemia screening.

When seconds matter - introducing a surgical salvage strategy by emergency robotic surgery: a review.

Robotic surgery has expanded minimally invasive options but introduces specific vulnerabilities during intraoperative emergencies. The physical separa...

Beyond fluorescence: A critical look at AI-powered brightfield analysis for T-cell killing assays.

This comment evaluates dela Cruz-Chuh et al.'s AI-based label-free workflow for analyzing T-cell mediated tumor killing via brightfield imaging. The s...

Exploring exosome-related genes as candidate biomarkers in primary immune thrombocytopenia through transcriptomics and preliminary experimental validation.

Primary Immune Thrombocytopenia (ITP) is an autoimmune disease characterized by thrombocytopenia and bleeding tendency. Exosomes mediate abnormal cros...

Machine learning-based models using preoperative imaging and clinical data to predict intraoperative rebleeding and functional recovery in intracerebral hemorrhage patients: a multicenter study.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with high mortality and disability. This study aimed to develop and validate mach...

Effect of a clinical decision support system on stroke care quality and outcomes in patients with acute ischaemic stroke (GOLDEN BRIDGE II): cluster randomised clinical trial.

OBJECTIVE: To evaluate the efficacy of a clinical decision support system (CDSS) on stroke care quality and clinical outcomes among patients with acut...

Cross-sectional evaluation of cardiovascular biological age using point-of-care ultrasound.

AIMS: Biological age is increasingly recognized as a superior predictor of morbidity, mortality, compared with chronological age. Artificial intellige...

Prediction of preterm and low birth weight risk using a physiology based artificial neural network integrating hematological, dental, and periodontal index markers: a cross sectional study based on machine learning.

Predicting toxicity and bioactivity of the chemical exposome: a case study for the blood exposome database.

Humans are exposed to thousands of chemicals throughout their life. Many of these chemicals are detected in blood and have been catalogued in the Bloo...

Automated multi-chemical dosing control based on machine learning for magnetic coagulation in aquaculture wastewater.

Magnetic coagulation using magnetic powder with polyaluminum chloride and polyacrylamide is a promising option for aquaculture wastewater treatment, y...