Hematology

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

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Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy.

Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions wi...

Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.

Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) ...

Coagulation Risk Predicting in Anticoagulant-Free Continuous Renal Replacement Therapy.

INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal b...

Comparative analysis of feature selection techniques for COVID-19 dataset.

In the context of early disease detection, machine learning (ML) has emerged as a vital tool. Featur...

The synchronous upregulation of a specific protein cluster in the blood predicts both colorectal cancer risk and patient immune status.

BACKGROUND: Early detection and treatment of colorectal cancer (CRC) is crucial for improving patien...

Learning control-ready forecasters for Blood Glucose Management.

Type 1 diabetes (T1D) presents a significant health challenge, requiring patients to actively manage...

Hierarchical Hybrid Networks for Automatic Pulmonary Blood Vessel Segmentation in Computed Tomography Images.

Pulmonary arterial hypertension (PAH) is considered the third most common cardiovascular disease aft...

Stress Classification and Vital Signs Forecasting for IoT-Health Monitoring.

Health monitoring embedded with intelligence is the demand of the day. In this era of a large popula...

Identification of Active Molecules against Thrombocytopenia through Machine Learning.

Thrombocytopenia, which is associated with thrombopoietin (TPO) deficiency, presents very limited tr...

Machine Learning-Driven Biomarker Discovery for Skeletal Complications in Type 1 Gaucher Disease Patients.

Type 1 Gaucher disease (GD1) is a rare, autosomal recessive disorder caused by glucocerebrosidase de...

Non-Contact Blood Pressure Estimation From Radar Signals by a Stacked Deformable Convolution Network.

This study introduces a contactless blood pressure monitoring approach that combines conventional ra...

DeepBP: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN.

INTRODUCTION: The blood-brain barrier (BBB) serves as a critical structural barrier and impedes the ...

Establishing reflex test rules for platelet fluorescent counting method using machine learning models on Sysmex XN-series hematology analyzer.

INTRODUCTION: The platelet fluorescent counting (PLT-F) method is utilized as a reflex test method f...

Could machine learning revolutionize how we treat immune thrombocytopenia?

The absence of reliable biomarkers in immune thrombocytopenia (ITP) complicates treatment choice, ne...

Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics.

Multiple sclerosis (MS) is a neurological disorder characterized by immune dysregulation. It begins ...

Soul: An OCTA dataset based on Human Machine Collaborative Annotation Framework.

Branch retinal vein occlusion (BRVO) is the most prevalent retinal vascular disease that constitutes...

Interpretation of acid-base metabolism on arterial blood gas samples via machine learning algorithms.

BACKGROUND: Arterial blood gas evaluation is crucial for critically ill patients, as it provides ess...

Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.

Acute respiratory distress syndrome (ARDS) is a devastating critical care syndrome with significant ...

Single-center outcomes of artificial intelligence in management of pulmonary embolism and pulmonary embolism response team activation.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites ...

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