Rheumatology

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

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Prediction and causal inference of hyperuricemia using gut microbiota.

Hyperuricemia (HUA) is a symptom of high blood uric acid (UA) levels, which causes disorders such as...

Weighted Gene Co-expression Network Analysis and Machine Learning Validation for Identifying Major Genes Related to Sjogren's Syndrome.

Sjogren's syndrome (SS) is an autoimmune disorder characterized by dry mouth and dry eyes. Its patho...

Integrated machine learning-based virtual screening and biological evaluation for identification of potential inhibitors against cathepsin K.

Cathepsin K is a type of cysteine proteinase that is primarily expressed in osteoclasts and has a ke...

Advances in artificial intelligence in thyroid-associated ophthalmopathy.

Thyroid-associated ophthalmopathy (TAO), also referred to as Graves' ophthalmopathy, is a medical co...

HBCVTr: an end-to-end transformer with a deep neural network hybrid model for anti-HBV and HCV activity predictor from SMILES.

Hepatitis B and C viruses (HBV and HCV) are significant causes of chronic liver diseases, with appro...

Predictive modeling of co-infection in lupus nephritis using multiple machine learning algorithms.

This study aimed to analyze peripheral blood lymphocyte subsets in lupus nephritis (LN) patients and...

DeepSeq2Drug: An expandable ensemble end-to-end anti-viral drug repurposing benchmark framework by multi-modal embeddings and transfer learning.

Drug repurposing is promising in multiple scenarios, such as emerging viral outbreak controls and co...

Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes.

At present, anti-cancer drug synergy therapy is one of the most important methods to overcome drug r...

Human-multimodal deep learning collaboration in 'precise' diagnosis of lupus erythematosus subtypes and similar skin diseases.

BACKGROUND: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of ...

DEEP-EP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery.

Epigenetic proteins (EP) play a role in the progression of a wide range of diseases, including autoi...

Impact of COVID-19 on arthritis with generative AI.

OBJECTIVE: The study aims to examine the effects of the COVID-19 pandemic on the prevalence of arthr...

Stack-AAgP: Computational prediction and interpretation of anti-angiogenic peptides using a meta-learning framework.

BACKGROUND: Angiogenesis plays a vital role in the pathogenesis of several human diseases, particula...

Exploring the impact of pathogenic microbiome in orthopedic diseases: machine learning and deep learning approaches.

Osteoporosis, arthritis, and fractures are examples of orthopedic illnesses that not only significan...

[Involvement of essential trace elements in the pathogenesis of thyroid diseases: diagnostic markers and analytical methods for determination].

AIM: To study the role of iodine, selenium and zinc in the pathogenesis of iodine deficiency and aut...

Innovations in Medicine: Exploring ChatGPT's Impact on Rare Disorder Management.

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of ...

Face anti-spoofing with cross-stage relation enhancement and spoof material perception.

Face Anti-Spoofing (FAS) seeks to protect face recognition systems from spoofing attacks, which is a...

Prediction of systemic lupus erythematosus-related genes based on graph attention network and deep neural network.

Systemic lupus erythematosus (SLE) is an autoimmune disorder intricately linked to genetic factors, ...

Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-...

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse predicti...

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