Hemophilia

FGFR1Pred: an artificial intelligence-based model for predicting fibroblast growth factor receptor 1 inhibitor.

Fibroblast growth factor receptors (FGFRs) are a family of cell surface receptors that bind to fibro...

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease ...

How can artificial intelligence help rehabilitation programs for people with hemophilia in the coming decades?

High accuracy epidermal growth factor receptor mutation prediction via histopathological deep learning.

BACKGROUND: The detection of epidermal growth factor receptor (EGFR) mutations in patients with non-...

A deep learning and docking simulation-based virtual screening strategy enables the rapid identification of HIF-1α pathway activators from a marine natural product database.

Artificial Intelligence is hailed as a cutting-edge technology for accelerating drug discovery effor...

Strategy toward Kinase-Selective Drug Discovery.

Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar ...

Development, validation, and evaluation of a deep learning model to screen cyclin-dependent kinase 12 inhibitors in cancers.

Deep learning-based in silico alternatives have been demonstrated to be of significant importance in...

A radiomics-based deep learning approach to predict progression free-survival after tyrosine kinase inhibitor therapy in non-small cell lung cancer.

BACKGROUND: The epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are a firs...

Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer.

AIM: To develop and validate a nomogram model that combines computed tomography (CT)-based radiologi...

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study.

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of...

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....

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...

Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmia diseases. Thromboe...