Hematology

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

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New Insights and Methods in the Approach to Thalassemia Major: The Lesson From the Case of Adrenal Insufficiency.

Thalassemia Major (TM) is a complex pathology that needs a highly skilled approach. Endocrine comor...

Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection.

Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and b...

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, a...

Machine learning detection of Atrial Fibrillation using wearable technology.

BACKGROUND: Atrial Fibrillation is the most common arrhythmia worldwide with a global age adjusted p...

First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws.

Obtaining venous access for blood sampling or intravenous (IV) fluid delivery is an essential first ...

Multi-media biomarkers: Integrating information to improve lead exposure assessment.

Exposure assessment traditionally relies on biomarkers that measure chemical concentrations in indiv...

A Deep Neural Network Application for Improved Prediction of [Formula: see text] in Type 1 Diabetes.

[Formula: see text] is a primary marker of long-term average blood glucose, which is an essential me...

Machine learning models for identifying preterm infants at risk of cerebral hemorrhage.

Intracerebral hemorrhage in preterm infants is a major cause of brain damage and cerebral palsy. The...

Predicting Chronic Subdural Hematoma Recurrence and Stroke Outcomes While Withholding Antiplatelet and Anticoagulant Agents.

The aging of the western population and the increased use of oral anticoagulation (OAC) and antipla...

Expression of Cytokines and Chemokines as Predictors of Stroke Outcomes in Acute Ischemic Stroke.

Ischemic stroke remains one of the most debilitating diseases and is the fifth leading cause of dea...

Clot Analog Attenuation in Non-contrast CT Predicts Histology: an Experimental Study Using Machine Learning.

Exact histological clot composition remains unknown. The purpose of this study was to identify the b...

Classification of white blood cells using capsule networks.

BACKGROUND: While the number and structural features of white blood cells (WBC) can provide importan...

Machine learning as new promising technique for selection of significant features in obese women with type 2 diabetes.

Background The global trend of obesity and diabetes is considerable. Recently, the early diagnosis a...

Prediction of blood pressure variability using deep neural networks.

PURPOSE: The purpose of our study was to predict blood pressure variability from time-series data of...

Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.

IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early ...

Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network.

BACKGROUND AND AIM: Detecting blood content in the gastrointestinal tract is one of the crucial appl...

Effects of aged garlic extract on arterial elasticity in a placebo-controlled clinical trial using EndoPATâ„¢ technology.

Cardiovascular diseases are the main cause of death in the industrialized world, with the main risk ...

Analyzing brain structural differences associated with categories of blood pressure in adults using empirical kernel mapping-based kernel ELM.

BACKGROUND: Hypertension increases the risk of angiocardiopathy and cognitive disorder. Blood pressu...

Diagnostic Value of Lesion-specific Measurement of Myocardial Blood Flow Using Hybrid PET/CT.

BACKGROUND: We evaluated whether lesion-specific measurement of myocardial blood flow (MBF) and flow...

Obstetric Hemorrhage Outcomes by Intrapartum Risk Stratification at a Single Tertiary Care Center.

Introduction Postpartum hemorrhage is a leading cause of maternal mortality worldwide. Performance o...

Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures.

OBJECTIVE: Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction,...

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