Hematology

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

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Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension.

Gravity, an invisible but constant force , challenges the regulation of blood pressure when transiti...

Deep learning segmentation-based bone removal from computed tomography of the brain improves subdural hematoma detection.

PURPOSE: Timely identification of intracranial blood products is clinically impactful, however the d...

A machine-learning-based algorithm for bone marrow cell differential counting.

BACKGROUND: Differential counting (DC) of different cell types in bone marrow (BM) aspiration smears...

MultiThal-classifier, a machine learning-based multi-class model for thalassemia diagnosis and classification.

BACKGROUND: The differential diagnosis between iron deficiency anemia (IDA) and thalassemia trait (T...

Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.

Sorting specific cells from heterogeneous samples is important for research and clinical application...

Optimizing anemia management using artificial intelligence for patients undergoing hemodialysis.

Patients with end-stage kidney disease (ESKD) frequently experience anemia, and maintaining hemoglob...

Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.

Viruses are widely recognized to be intricately associated with both solid and hematological maligna...

HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data.

In case-control single-cell RNA-seq studies, sample-level labels are transferred onto individual cel...

An enhanced machine learning algorithm for type 2 diabetes prognosis with a detailed examination of Key correlates.

This study aimed to construct a high-performance prediction and diagnosis model for type 2 diabetic ...

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

CONTEXT: This study investigates the potential of leveraging molecular properties, as determined by ...

Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.

INTRODUCTION: The mortality rate among older people infected with severe acute respiratory syndrome ...

Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG.

This work reports an efficient method to detect SARS-CoV-2 antibodies in blood samples based on SERS...

Trends in the prevalence of osteoporosis and effects of heavy metal exposure using interpretable machine learning.

There is limited evidence that heavy metals exposure contributes to osteoporosis. Multi-parameter sc...

VCU-Net: a vascular convolutional network with feature splicing for cerebrovascular image segmentation.

Cerebrovascular image segmentation is one of the crucial tasks in the field of biomedical image proc...

Enhancing endometrial cancer detection: Blood serum intrinsic fluorescence data processing and machine learning application.

Endometrial cancer (EC) is the most prevalent cancer within the female reproductive system in develo...

Assessment of machine learning classifiers for predicting intraoperative blood transfusion in non-cardiac surgery.

BACKGROUND: This study aimed to develop a machine learning classifier for predicting intraoperative ...

Optimized deep learning networks for accurate identification of cancer cells in bone marrow.

Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans ...

Big data and artificial intelligence applied to blood and CSF fluid biomarkers in multiple sclerosis.

Artificial intelligence (AI) has meant a turning point in data analysis, allowing predictions of uns...

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