EXPLORING THE EFFICACY AND MOLECULAR PATHWAYS OF ACUPUNCTURE IN RHEUMATOID ARTHRITIS USING ARTIFICIAL INTELLIGENCE TECHNIQUES
: https://doi.org/10.65725/JCISE/2/2/010
JOURNAL OF COMPUTATIONAL INTELLIGENCE SCIENCE AND ENGINEERING (JCISE)
ISSN: 3107-8168
Volume 2 Issue 2, Apr-June 2026

Abstract: 
Rheumatoid arthritis (RA) is a chronic autoimmune disorder that affects millions of people worldwide, causing joint inflammation, pain, and progressive disability. While conventional treatments such as disease-modifying antirheumatic drugs and biologics have improved patient outcomes, many individuals continue to experience side effects, incomplete remission, or treatment resistance. Acupuncture, an ancient therapeutic practice rooted in Traditional Chinese Medicine, has gained increasing attention as a complementary treatment for RA, with growing clinical evidence supporting its analgesic and anti-inflammatory effects. However, the underlying molecular mechanisms remain poorly understood, largely because they involve complex interactions across multiple biological pathways. This study applies artificial intelligence techniques to explore both the clinical efficacy and the molecular pathways of acupuncture in RA. We integrated clinical trial data from 2,340 patients with network pharmacology and gene expression datasets to build a predictive and explanatory framework. A combination of deep neural networks, graph attention networks, and pathway enrichment analysis was used to identify key molecular targets and predict patient response. The model achieved a treatment response prediction accuracy of 89.4% and identified several biologically meaningful pathways, including the TNF signalling pathway, the JAK-STAT pathway, and the NF-κB inflammatory cascade. These findings provide a clearer picture of how acupuncture may modulate immune and inflammatory responses in RA patients, while also offering a data-driven tool for personalized treatment planning. The study demonstrates the value of combining AI with traditional medicine research to uncover mechanisms that have long remained difficult to study through conventional methods alone.

Authors: Abdul Kuthus A M, Dr. N. Zackariah 

Keywords: Acupuncture, Rheumatoid Arthritis, Artificial Intelligence, Molecular Pathways,  Deep Learning, Network Pharmacology.