AIMC Topic: Arthritis, Rheumatoid

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Rapid screening for autoimmune diseases using Fourier transform infrared spectroscopy and deep learning algorithms.

Frontiers in immunology
INTRODUCE: Ankylosing spondylitis (AS), rheumatoid arthritis (RA), and osteoarthritis (OA) are three rheumatic immune diseases with many common characteristics. If left untreated, they can lead to joint destruction and functional limitation, and in s...

Rapid diagnosis of rheumatoid arthritis and ankylosing spondylitis based on Fourier transform infrared spectroscopy and deep learning.

Photodiagnosis and photodynamic therapy
OBJECTIVE: Rheumatoid arthritis and Ankylosing spondylitis are two common autoimmune inflammatory rheumatic diseases that negatively affect activities of daily living and can lead to structural and functional disability, reduced quality of life. Here...

Assessing the accuracy and completeness of artificial intelligence language models in providing information on methotrexate use.

Rheumatology international
We aimed to assess Large Language Models (LLMs)-ChatGPT 3.5-4, BARD, and Bing-in their accuracy and completeness when answering Methotrexate (MTX) related questions for treating rheumatoid arthritis. We employed 23 questions from an earlier study rel...

Automatic evaluation of atlantoaxial subluxation in rheumatoid arthritis by a deep learning model.

Arthritis research & therapy
BACKGROUND: This work aims to develop a deep learning model, assessing atlantoaxial subluxation (AAS) in rheumatoid arthritis (RA), which can often be ambiguous in clinical practice.

Multiple switching between the biosimilar adalimumab PF-06410293 and reference adalimumab in patients with active rheumatoid arthritis: a phase 3, open-label, randomised, parallel-group study.

The Lancet. Rheumatology
BACKGROUND: An adalimumab biosimilar with an interchangeability designation could increase access to effective treatment for more patients. We aimed to assess the interchangeability of adalimumab biosimilar PF-06410293 (adalimumab-afzb) and reference...

Deep learning discrimination of rheumatoid arthritis from osteoarthritis on hand radiography.

Skeletal radiology
PURPOSE: To develop a deep learning model to distinguish rheumatoid arthritis (RA) from osteoarthritis (OA) using hand radiographs and to evaluate the effects of changing pretraining and training parameters on model performance.

Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs.

PLoS computational biology
Cycling of biologic or targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) in rheumatoid arthritis (RA) patients due to non-response is a problem preventing and delaying disease control. We aimed to assess and validate treatment res...

Detecting hand joint ankylosis and subluxation in radiographic images using deep learning: A step in the development of an automatic radiographic scoring system for joint destruction.

PloS one
We propose a wrist joint subluxation/ankylosis classification model for an automatic radiographic scoring system for X-ray images. In managing rheumatoid arthritis, the evaluation of joint destruction is important. The modified total Sharp score (mTS...

Deep learning-based automatic-bone-destruction-evaluation system using contextual information from other joints.

Arthritis research & therapy
BACKGROUND: X-ray images are commonly used to assess the bone destruction of rheumatoid arthritis. The purpose of this study is to propose an automatic-bone-destruction-evaluation system fully utilizing deep neural networks (DNN). This system detects...