Rheumatology

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

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From Web to RheumaLpack: Creating a Linguistic Corpus for Exploitation and Knowledge Discovery in Rheumatology.

This study introduces RheumaLinguisticpack (RheumaLpack), the first specialised linguistic web corpu...

The emerging paradigm in pediatric rheumatology: harnessing the power of artificial intelligence.

Artificial intelligence algorithms, with roots extending into the past but experiencing a resurgence...

Development of a deep-learning model tailored for HER2 detection in breast cancer to aid pathologists in interpreting HER2-low cases.

AIMS: Over 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breas...

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...

Molecular docking aided machine learning for the identification of potential VEGFR inhibitors against renal cell carcinoma.

Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (...

Multimodal Machine Learning-Based Marker Enables Early Detection and Prognosis Prediction for Hyperuricemia.

Hyperuricemia (HUA) has emerged as the second most prevalent metabolic disorder characterized by pro...

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

To achieve the accuracy and anti-interference of the motion control of the soft robot more effective...

Evaluation of Serum Visfatin as a Biomarker of Lupus Nephritis in Egyptian Patients with Systemic Lupus Erythematosus.

One of the most significant consequences of systemic lupus erythematosus (SLE) is lupus nephritis (L...

A high hydrophobic moment arginine-rich peptide screened by a machine learning algorithm enhanced ADC antitumor activity.

Cell-penetrating peptides (CPPs) with better biomolecule delivery properties will expand their clini...

Artificial Intelligence-Powered Molecular Docking and Steered Molecular Dynamics for Accurate scFv Selection of Anti-CD30 Chimeric Antigen Receptors.

Chimeric antigen receptor (CAR) T cells represent a revolutionary immunotherapy that allows specific...

Predicting renal damage in children with IgA vasculitis by machine learning.

BACKGROUND: Children with IgA Vasculitis (IgAV) may develop renal complications, which can impact th...

Improved prediction of anti-angiogenic peptides based on machine learning models and comprehensive features from peptide sequences.

Angiogenesis is a key process for the proliferation and metastatic spread of cancer cells. Anti-angi...

Artificial intelligence in autoimmune bullous dermatoses.

Dermatologists treating patients with autoimmune bullous dermatoses (AIBDs), as well as the patients...

The state of artificial intelligence for systemic dermatoses: Background and applications for psoriasis, systemic sclerosis, and much more.

Artificial intelligence (AI) has been steadily integrated into dermatology, with AI platforms alread...

From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in ...

A deep-learning-based model for assessment of autoimmune hepatitis from histology: AI(H).

Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results...

Machine learning and artificial intelligence within pediatric autoimmune diseases: applications, challenges, future perspective.

INTRODUCTION: Autoimmune disorders affect 4.5% to 9.4% of children, significantly reducing their qua...

Machine learning models predicts risk of proliferative lupus nephritis.

OBJECTIVE: This study aims to develop and validate machine learning models to predict proliferative ...

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