Hematology

Latest AI and machine learning research in hematology for healthcare professionals.

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Can polycythaemia vera disease be predicted from haematologic parameters? A machine learning-based study.

AIMS: The aim of this research is to diagnose polycythaemia vera (PV) disease using different machin...

Digital Pathology in Hematopathology: From Vision to Deployment.

Digital pathology (DP) has evolved alongside other technical advances, transforming our daily lives ...

Multi-omic profiling reveals age-specific blood biomarkers and aging-driven B Cell remodeling in osteoarthritis.

BACKGROUND: Osteoarthritis (OA) pathogenesis involves age-related immune dysregulation, yet non-inva...

Multiclass classification of thalassemia types using complete blood count and HPLC data with machine learning.

Mild to severe anemia is caused by thalassemia, a common genetic disorder affecting over 100 countri...

Enhanced gastrointestinal disease classification using a convvit hybrid model on endoscopic images.

Endoscopy is a procedure that allows examination of the gastrointestinal system, including the stoma...

Advances in Nature-Inspired Particles for Bioanalytical Applications.

Nature has evolved sophisticated prototypes to achieve functions from efficient separation to select...

Analysis of aPTT predictors after unfractionated heparin administration in intensive care units using machine learning models.

OBJECTIVES: Predicting optimal coagulation control using heparin in intensive care units (ICUs) rema...

Design of a Wearable Finger PPG-Based Blood Glucose Monitor.

PURPOSE: Blood glucose monitoring is crucial for controlling diabetes. However, traditional fingerti...

Functionalized Nanofinger Enhances Pretrained Language Model Performance for Ultrafast Early Warning of Heart Attacks.

Heart attacks are the leading cause of death worldwide, which means an accurate early warning system...

Prediction of birthweight with early and mid-pregnancy antenatal markers utilising machine learning and explainable artificial intelligence.

Low birthweight (LBW) is a significant health challenge worldwide, as these neonates experience both...

Artificial Intelligence for Tumor [F]FDG PET Imaging: Advancements and Future Trends - Part II.

The integration of artificial intelligence (AI) into [F]FDG PET/CT imaging continues to expand, offe...

Using Machine-Learning to Identify Differences in the Association between Blood-Based Biomarkers and Later Life Health Across Race and Ethnicity.

Increasingly, biomarkers are used to understand health and health inequalities among older adults. C...

Machine Learning for Detecting Iron Deficiency through Comprehensive Blood Analysis.

BACKGROUND: Iron deficiency (ID) is a prevalent global health issue with a major impact on well-bein...

Deep learning reconstruction enhances image quality in contrast-enhanced CT venography for deep vein thrombosis.

PURPOSE: This study aimed to evaluate and compare the diagnostic performance and image quality of de...

Microbiome-based prediction of allogeneic hematopoietic stem cell transplantation outcome.

BACKGROUND: Allogeneic hematopoietic stem cell transplantation (HSCT) is potentially curative for he...

Automatic selection of optimal TI for flow-independent dark-blood delayed-enhancement MRI.

PURPOSE: Propose and evaluate an automatic approach for predicting the optimal inversion time (TI) f...

Screening for endometriosis: A scoping review of screening measures that could support early diagnosis.

BACKGROUND: Endometriosis is prevalent in approximately 6-10% of all women of reproductive age and i...

The Application of Artificial Intelligence-Based Bone Marrow Cell Analysis System in Pediatric Hematological Diseases.

INTRODUCTION: The clinical diagnosis of hematological diseases depends on the differential count of ...

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