Hematology

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

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Machine learning-derived peripheral blood transcriptomic biomarkers for early lung cancer diagnosis: Unveiling tumor-immune interaction mechanisms.

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection...

Artificial neural network-based prediction of multiple sclerosis using blood-based metabolomics data.

Multiple sclerosis (MS) remains a challenging neurological condition for diagnosis and management an...

Machine learning assisted rapid approach for quantitative prediction of biochemical parameters of blood serum with FTIR spectroscopy.

This study develops regression models for predicting blood biochemical data using Fourier-transform ...

Evaluating retinal blood vessels for predicting white matter hyperintensities in ischemic stroke: A deep learning approach.

OBJECTIVE: This study aims to investigate whether a deep learning approach incorporating retinal blo...

GloGen: PPG prompts for few-shot transfer learning in blood pressure estimation.

With the rapid advancements in machine learning, its applications in the medical field have garnered...

Comparing Human-Level and Machine Learning Model Performance in White Blood Cell Morphology Assessment.

INTRODUCTION: There is an increasing research focus on the role of machine learning in the haematolo...

Constructing a visual detection model for floc settling velocity using machine learning.

Optimizing the dosage of coagulant is a time-consuming process, and real-time evaluation of floc set...

Peripheral Blood Mononuclear Cell Biomarkers for Major Depressive Disorder: A Transcriptomic Approach.

Major depressive disorder (MDD) is a complex condition characterized by persistent depressed mood, ...

Predicting Individual Treatment Effects to Determine Duration of Dual Antiplatelet Therapy After Stent Implantation.

BACKGROUND: After coronary stent implantation, prolonged dual antiplatelet therapy (DAPT) increases ...

Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.

Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable...

Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.

BACKGROUNDS: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the dise...

Machine-learning based prediction model for acute kidney injury induced by multiple wasp stings.

Acute kidney injury (AKI) following multiple wasp stings is a severe complication with potentially p...

A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly...

BSNEU-net: Block Feature Map Distortion and Switchable Normalization-Based Enhanced Union-net for Acute Leukemia Detection on Heterogeneous Dataset.

Acute leukemia is characterized by the swift proliferation of immature white blood cells (WBC) in th...

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