Hematology

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

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Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection.

OBJECTIVE: Measurement and monitoring of blood pressure are of great importance for preventing disea...

An analysis of the influence of transfer learning when measuring the tortuosity of blood vessels.

BACKGROUND AND OBJECTIVE: Convolutional Neural Networks (CNNs) can provide excellent results regardi...

Accurate classification of white blood cells by coupling pre-trained ResNet and DenseNet with SCAM mechanism.

BACKGROUND: Via counting the different kinds of white blood cells (WBCs), a good quantitative descri...

Detection of WBC, RBC, and Platelets in Blood Samples Using Deep Learning.

A blood count is one of the most important diagnostic tools in medicine and one of the most common p...

Provisional Decision-Making for Perioperative Blood Pressure Management: A Narrative Review.

Blood pressure (BP) is a basic determinant for organ blood flow supply. Insufficient blood supply wi...

Leukocyte Segmentation Method Based on Adaptive Retinex Correction and U-Net.

To address the issues of uneven illumination and inconspicuous leukocyte properties in the gathered ...

Early Diagnosis of Retinal Blood Vessel Damage via Deep Learning-Powered Collective Intelligence Models.

Early diagnosis of retinal diseases such as diabetic retinopathy has had the attention of many resea...

Explainable Transformer-Based Deep Learning Model for the Detection of Malaria Parasites from Blood Cell Images.

Malaria is a life-threatening disease caused by female anopheles mosquito bites. Various plasmodium ...

DNL-Net: deformed non-local neural network for blood vessel segmentation.

BACKGROUND: The non-local module has been primarily used in literature to capturing long-range depen...

Prediction of blood pressure changes associated with abdominal pressure changes during robotic laparoscopic low abdominal surgery using deep learning.

BACKGROUND: Intraoperative hypertension and blood pressure (BP) fluctuation are known to be associat...

See-Through Vision With Unsupervised Scene Occlusion Reconstruction.

Among the greatest of the challenges of minimally invasive surgery (MIS) is the inadequate visualisa...

Heterogeneity in Blood Biomarker Trajectories After Mild TBI Revealed by Unsupervised Learning.

Concussions, also known as mild traumatic brain injury (mTBI), are a growing health challenge. Appro...

Blood metabolic signatures of hikikomori, pathological social withdrawal.

BACKGROUND: A severe form of pathological social withdrawal, 'hikikomori,' has been acknowledged in ...

Integrated Learning Model-Based Assessment of Enteral Nutrition Support in Neurosurgical Intensive Care Patients.

To observe the clinical efficacy of early enteral nutrition application in critically ill neurosurgi...

Deep compartment models: A deep learning approach for the reliable prediction of time-series data in pharmacokinetic modeling.

Nonlinear mixed effect (NLME) models are the gold standard for the analysis of patient response foll...

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