Application Of Deep Learning Techniques For Effective Assessment And Prediction Of Arthritis In Aged People
Rohini C1, Gowrishankar S2
1Rohini C, Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru, India.
2Gowrishankar S, Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2299-2303 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8604088619/2019©BEIESP | DOI: 10.35940/ijeat.F8604.088619
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Arthritis is an autoimmune disorder characterized by chronic synovial inflammation mainly leading to the destruction of joints and bone erosions. In aged people, arthritis is more common than any other disease, and it causes pain in the musculoskeletal system that lowers the quality of life of patients. The use of deep learning in medicine is increasing and has provided new avenues for research into a number of diseases. In this paper, we are using deep learning for detection of arthritis in finger joints from X-ray images of hand based on convolutional neural networks. For training 70 X-ray pictures are taken and for testing 10 X-ray pictures are taken. This system achieved more accuracy for test data sets. The proposed method will aid clinical researchers to learn more on arthritis.
Keywords: Arthritis, Deep Learning, Convolution neural network, Python, TensorFlow.