A survey of artificial intelligence in rheumatoid arthritis

Jiaqi Wang; Yu Tian; Tianshu Zhou; Danyang Tong; Jing Ma; Jingsong Li

doi:10.2478/rir-2023-0011

A survey of artificial intelligence in rheumatoid arthritis

Rheumatol Immunol Res. 2023 Jul 22;4(2):69-77. doi: 10.2478/rir-2023-0011. eCollection 2023 Jun.

Authors

Jiaqi Wang¹, Yu Tian², Tianshu Zhou¹, Danyang Tong¹, Jing Ma¹, Jingsong Li^{1

2}

Affiliations

¹ Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou 311121, Zhejiang Province, China.
² Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, Zhejiang Province, China.

Abstract

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.

Keywords: artificial intelligence; disease management; early diagnosis; early intervention; rheumatoid arthritis.

Grants and funding

This work was supported by the National Key Research and Development Program of China (No. 2022YFC2504605), the National Natural Science Foundation of China (No. 82172069), the Key Research Project of Zhejiang Lab Grants (No. 2022ND0AC01).