@InProceedings{Madaan2019, author = {Vishu Madaan and Rupinder Kaur and Prateek Agrawal}, booktitle = {2019 4th International Conference on Information Systems and Computer Networks (ISCON)}, title = {{Rheumatoid Arthritis anticipation using Adaptive Neuro Fuzzy Inference System}}, year = {2019}, month = nov, pages = {340--346}, publisher = {IEEE}, abstract = {A state of discomfort is known as a disease, also termed as illness or sickness. When the tiniest living things like virus enters our body, it reacts with the cells of the body and results an illness. The Arthritis is very problematic to early forecast. It nurtures with the age and related to the large and small joint pain. The Rheumatoid Arthritis (RA) is chronic disease, its long-term auto-immune and inflammatory disease which damages many joints tissues. It occurs when immune system can't distinguish the cells and tissues. The ANFIS model is used for the prediction of the RA in human mortals. A complete process is mentioned in this study, which helps to a technique for the diagnosis of the Rheumatoid Arthritis in human beings with accuracy 93.5%. This diagnosis is made on the bases of 12 symptoms of RA in human lives like age, stiffness, joint deformity, ESR, CRP, WBC, Uric Acid etc. This paper also compares the ANFIS with Naive Bayes, Bagging algorithm and KNN classifiers.}, doi = {10.1109/iscon47742.2019.9036297}, keywords = {Disease Diagnosis, Arthritis Symptoms, Arthritis Prediction, KNN Classifier, ANFIS, Naive Bayes Classification}, url = {https://ieeexplore.ieee.org/document/9036297} }