A survey of artificial intelligence in rheumatoid arthritis.
Jiaqi WangYu TianTianshu ZhouDanyang TongJing MaJing-Song LiPublished in: Rheumatology and immunology research (2023)
The article offers a survey of currently notable artificial intelligence methods (released between 2019-2023), with a particular emphasis on the latest advancements in detecting rheumatoid arthritis (RA) at an early stage, providing early treatment, and managing the disease. We discussed challenges in these areas followed by specific artificial intelligence (AI) techniques and summarized advances, relevant strengths, and obstacles. Overall, the application of AI in the fields of RA has the potential to enable healthcare professionals to detect RA at an earlier stage, thereby facilitating timely intervention and better disease management. However, more research is required to confirm the precision and dependability of AI in RA, and several problems such as technological and ethical concerns related to these approaches must be resolved before their widespread adoption.
Keyphrases
- artificial intelligence
- rheumatoid arthritis
- disease activity
- machine learning
- big data
- early stage
- deep learning
- ankylosing spondylitis
- interstitial lung disease
- randomized controlled trial
- systemic lupus erythematosus
- mental health
- systemic sclerosis
- risk assessment
- sentinel lymph node
- lymph node
- combination therapy
- neoadjuvant chemotherapy