Hematology

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

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Shengxuebao Mixture improves carboplatin-induced anemia by inhibiting apoptosis and ferroptosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Shengxuebao Mixture (SXB) is a traditional Chinese medicine which ha...

Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.

Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-thre...

An Early Thyroid Screening Model Based on Transformer and Secondary Transfer Learning for Chest and Thyroid CT Images.

IntroductionThyroid cancer is a common malignant tumor, and early diagnosis and timely treatment are...

Natural language processing for identifying major bleeding risk in hospitalised medical patients.

BACKGROUND: Major bleeding is a severe complication in critically ill medical patients, resulting in...

O blood usage trends in the pediatric population 2015-2019: A multi-institutional analysis.

BACKGROUND: In 2019, AABB released the bulletin "Recommendations on the Use of Group O Red Blood Cel...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Limited research exists on the association between depression and heavy metal exposure. This study a...

Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.

Gold nanoparticles (GNPs), which appear red, are widely used as labels in lateral flow assays (LFAs)...

Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis.

Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is sig...

A prospective study for the examination of peripheral blood smear samples in pediatric population using artificial intelligence.

BACKGROUND/AIM: Peripheral blood smear (PBS) and bone marrow aspiration are gold standards of manual...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mor...

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematolo...

Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of ...

Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.

Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasi...

Machine learning prediction of preterm birth in women under 35 using routine biomarkers in a retrospective cohort study.

Preterm birth (PTB), defined as delivery before 37 weeks, affects 15 million infants annually, accou...

Prediction model of gastrointestinal tumor malignancy based on coagulation indicators such as TEG and neural networks.

OBJECTIVES: Accurate determination of gastrointestinal tumor malignancy is a crucial focus of clinic...

Machine Learning-Based VO Estimation Using a Wearable Multiwavelength Photoplethysmography Device.

The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minu...

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