Hematology

Development and internal validation of a machine learning-based model to predict 1-year all-cause mortality in patients with gastrointestinal bleeding with type 2 diabetes.

Development and validation of an interpretable machine learning model integrating inflammatory blood biomarkers for predicting postoperative breast cancer-related lymphedema: A prospective cohort study.

BACKGROUND: Breast cancer-related lymphedema is a frequent and debilitating complication. Early iden...

A MULTIMODAL STOOL RNA, FIT AND MACHINE LEARNING CONCEPT FOR DETECTION OF ADVANCED PRECANCEROUS LESIONS AND COLORECTAL CANCER.

Accurate and effective early detection of colorectal cancer (CRC) and advanced precancerous lesions ...

A deep learning pipeline for mapping in situ network-level neurovascular coupling in multi-photon fluorescence microscopy.

Functional hyperemia is a well-established hallmark of healthy brain function, whereby local brain b...

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 imm...

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 pa...

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...

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 w...

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

Coronavirus disease 2019 (COVID-19)-associated coagulopathy (CAC) is a thromboinflammatory syndrome ...

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...

Fundamentals of big data and artificial intelligence in transfusion medicine.

Within the digital transformation of medicine, transfusion medicine has quietly become a big-data di...

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 ...

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 duri...

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...

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 disabil...

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 qual...

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, com...

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 dete...