Hematology

Hemophilia

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

6,132 articles
Stay Ahead - Weekly Hemophilia research updates
Subscribe
Browse Specialties
Showing 190-210 of 6,132 articles
Generative deep learning enables the discovery of a potent and selective RIPK1 inhibitor.

The retrieval of hit/lead compounds with novel scaffolds during early drug development is an importa...

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy....

Selective Inhibitor Design for Kinase Homologs Using Multiobjective Monte Carlo Tree Search.

Designing highly selective molecules for a drug target protein is a challenging task in drug discove...

Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen.

SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known ...

The current role of artificial intelligence in hemophilia.

INTRODUCTION: The utilization of artificial intelligence (AI) in hemophilia is still in its early ph...

Risk Factors Analysis of Surgical Infection Using Artificial Intelligence: A Single Center Study.

Surgical site infections (SSIs) have a major role in the evolution of medical care. Despite centuri...

Deep learning for topical trend discovery in online discourse about Pre-Exposure Prophylaxis (PrEP).

Pre-Exposure Prophylaxis (PrEP) interventions are increasingly prevalent on social media. These data...

Development of Lymphopenia during Therapy with Immune Checkpoint Inhibitors Is Associated with Poor Outcome in Metastatic Cutaneous Melanoma.

Predictive markers for immune checkpoint inhibitor (ICI) therapy are needed. Thus, baseline blood co...

Anti-CRISPR prediction using deep learning reveals an inhibitor of Cas13b nucleases.

As part of the ongoing bacterial-phage arms race, CRISPR-Cas systems in bacteria clear invading phag...

Deep compartment models: A deep learning approach for the reliable prediction of time-series data in pharmacokinetic modeling.

Nonlinear mixed effect (NLME) models are the gold standard for the analysis of patient response foll...

An integrated network representation of multiple cancer-specific data for graph-based machine learning.

Genomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Seve...

DNA Input Classification by a Riboregulator-Based Cell-Free Perceptron.

The ability to recognize molecular patterns is essential for the continued survival of biological or...

An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension.

The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (...

History Dependence in a Chemical Reaction Network Enables Dynamic Switching.

This work describes an enzymatic autocatalytic network capable of dynamic switching under out-of-equ...

TIMP-1: A Circulating Biomarker for Pulmonary Hypertension Diagnosis Among Chronic Obstructive Pulmonary Disease Patients.

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD)...

A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell pr...

Browse Specialties