Hematology

Hemophilia

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

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Showing 106-126 of 6,132 articles
as a Novel Biomarker for Colon Cancer Bone Metastasis with Machine Learning and Immunohistochemistry Validation.

Bone metastasis (BM) is a serious clinical symptom of advanced colorectal cancer. However, there is...

Wee1 inhibitor optimization through deep-learning-driven decision making.

Deep learning has gained increasing attention in recent years, yielding promising results in hit scr...

Bowel preparation before elective right colectomy: Multitreatment machine-learning analysis on 2,617 patients.

BACKGROUND: In the worldwide, real-life setting, some candidates for right colectomy still receive n...

Interpretable machine learning model predicting immune checkpoint inhibitor-induced hypothyroidism: A retrospective cohort study.

Hypothyroidism is a known adverse event associated with the use of immune checkpoint inhibitors (ICI...

Deep-Learning-Driven Discovery of SN3-1, a Potent NLRP3 Inhibitor with Therapeutic Potential for Inflammatory Diseases.

The NLRP3 inflammasome plays a central role in the pathogenesis of various intractable human disease...

Prediction of Inhibitory Activity against the MATE1 Transporter via Combined Fingerprint- and Physics-Based Machine Learning Models.

Renal secretion plays an important role in excretion of drug from the kidney. Two major transporters...

Development of a novel prognostic signature derived from super-enhancer-associated gene by machine learning in head and neck squamous cell carcinoma.

Dysregulated super-enhancer (SE) results in aberrant transcription that drives cancer initiation and...

Novel molecular inhibitor design for Plasmodium falciparum Lactate dehydrogenase enzyme using machine learning generated library of diverse compounds.

Generative machine learning models offer a novel strategy for chemogenomics and de novo drug design,...

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potent...

Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy.

We present a study where predictive mechanistic modeling is combined with deep learning methods to p...

Development and validation of a machine learning-based, point-of-care risk calculator for post-ERCP pancreatitis and prophylaxis selection.

BACKGROUND AND AIMS: A robust model of post-ERCP pancreatitis (PEP) risk is not currently available....

Redefining a new frontier in alkaptonuria therapy with AI-driven drug candidate design via innovation.

A rare metabolic condition called alkaptonuria (AKU) is caused by a decrease in homogentisate 1,2 di...

Construction of IRAK4 inhibitor activity prediction model based on machine learning.

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a crucial serine/threonine protein kinase that...

Synthesis, Docking, and Machine Learning Studies of Some Novel Quinolinesulfonamides-Triazole Hybrids with Anticancer Activity.

In the presented work, a series of 22 hybrids of 8-quinolinesulfonamide and 1,4-disubstituted triazo...

Discovery of a Novel and Potent LCK Inhibitor for Leukemia Treatment via Deep Learning and Molecular Docking.

The lymphocyte-specific protein tyrosine kinase (LCK) plays a crucial role in both T-cell developmen...

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