Hematology

Hemophilia

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

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Development of an artificial intelligence-enhanced warfarin interaction checker platform.

Warfarin is a common anticoagulant drug for thrombo-prophylaxis in stroke and venous thromboembolism...

Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.

We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP...

Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control.

Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and ...

Artificial intelligence system for predicting hand-foot skin reaction induced by vascular endothelial growth factor receptor inhibitors.

Hand-foot skin reaction (HFSR) is a common adverse effect of vascular endothelial growth factor rece...

Integrated AI and machine learning pipeline identifies novel WEE1 kinase inhibitors for targeted cancer therapy.

The dysregulation of the cell cycle in cancer underscores the therapeutic potential of targeting WEE...

Enhancing HCV NS3 Inhibitor Classification with Optimized Molecular Fingerprints Using Random Forest.

The classification of Hepatitis C virus (HCV) NS3 inhibitors is essential for identifying potential ...

Artificial intelligence and whole slide imaging, a new tool for the microsatellite instability prediction in colorectal cancer: Friend or foe?

Colorectal cancer (CRC) is the third most common and second most deadly cancer worldwide. Despite ad...

Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC.

BACKGROUND: Immune checkpoint inhibitors (CPIs) have revolutionized cancer therapy for several tumor...

Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography.

PURPOSE: Primary barriers to application of immune checkpoint inhibitor (ICI) therapy for cancer inc...

A deep-learning model for predicting tyrosine kinase inhibitor response from histology in gastrointestinal stromal tumor.

Over 90% of gastrointestinal stromal tumors (GISTs) harbor mutations in KIT or PDGFRA that can predi...

Optimizing kinase and PARP inhibitor combinations through machine learning and in silico approaches for targeted brain cancer therapy.

The drug combination is an attractive approach for cancer treatment. PARP and kinase inhibitors have...

Identification of dequalinium as a potent inhibitor of human organic cation transporter 2 by machine learning based QSAR model.

Human organic cation transporter 2 (hOCT2/SLC22A2) is a key drug transporter that facilitates the tr...

Research on detection methods of related substances and degradation products of the antitumor drug selpercatinib.

BACKGROUND: Selpercatinib, a selective RET kinase inhibitor, is approved for treating various cancer...

CA19-9-related macrophage polarization drives poor prognosis in HCC after immune checkpoint inhibitor treatment.

BACKGROUND: Elevated levels of carbohydrate antigen 19-9 (CA19-9) levels are known to worsen outcome...

Integrating machine learning and structural dynamics to explore B-cell lymphoma-2 inhibitors for chronic lymphocytic leukemia therapy.

Chronic lymphocytic leukemia (CLL) is a malignancy caused by the overexpression of the anti-apoptoti...

Applying artificial intelligence to uncover the genetic landscape of coagulation factors.

Artificial intelligence (AI) is rapidly advancing our ability to identify and interpret genetic vari...

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