Hematology

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

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Machine learning to forecast rituximab responses for paediatric immune thrombocytopenia: Forging a path towards personalized medical care.

Primary immune thrombocytopenia (ITP) is an autoimmune disorder characterized by decreased platelet ...

Development and external validation of a machine learning model for predicting drug-induced immune thrombocytopenia in a real-world hospital cohort.

BACKGROUND: Drug-induced immune thrombocytopenia (DITP) is a rare but potentially life-threatening a...

Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.

BACKGROUND: Hemorrhage is a prevalent and critical condition in the intensive care unit (ICU), chara...

Domain-incremental white blood cell classification with privacy-aware continual learning.

White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medica...

Advantages of AI-based whole blood film scanning for blast detection in markedly leucopenic blood films.

To evaluate performance of AI-assisted blast detection via whole blood film scanning in cases of sev...

Exploring novel molecular mechanisms underlying recurrent pregnancy loss in decidual tissues.

Recurrent pregnancy loss (RPL), which affects approximately 2.5% of reproductive-aged women, remains...

Construction of a Machine Learning-Based Clopidogrel Resistance Risk Prediction Model.

Clopidogrel is extensively utilized for the prevention and treatment of cardiovascular, cerebrovascu...

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the genera...

Integrated clinicopathological-radiomic-blood model for glioma survival prediction via machine learning: a multicenter cohort study.

BACKGROUND: Glioma is characterized by a poor prognosis and limited possibilities for treatment. Pre...

SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction.

BACKGROUND: Sepsis is a life-threatening condition that is one of the major causes of death worldwid...

How machine learning on real world clinical data improves adverse event recording for endoscopy.

Endoscopic interventions are essential for diagnosing and treating gastrointestinal conditions. Accu...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracereb...

Recent advancement in endoscopic diagnosis for risk stratification of gastric cancer.

Approximately 90% of cases of gastric cancer (GC) are caused by Helicobacter pylori infection, and s...

Prediction and characterisation of the human B cell response to a heterologous two-dose Ebola vaccine.

Ebola virus disease (EVD) outbreaks are increasing, posing significant threats to affected communiti...

Advantages and effectiveness of AI three-dimensional reconstruction technology in the preoperative planning of total hip arthroplasty.

In order to explore the application effect of artificial intelligence (AI) 3D reconstruction technol...

Inhibiting heme piracy by pathogenic Escherichia coli using de novo-designed proteins.

Iron is an essential nutrient for most bacteria and is often growth-limiting during infection, due t...

Evolving Blood Pressure Estimation: From Feature Analysis to Image-Based Deep Learning Models.

Traditional cuffless blood pressure (BP) estimation methods often require collecting physiological s...

Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model.

Intravenous immunoglobulin (IVIG) has been established as the first-line therapy for Kawasaki diseas...

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