The week's pick
Reseach Article
Automated Cancer Detection using Machine Learning and Image Processing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 30 |
| Year of Publication: 2022 |
| Authors: H.M.U.S.S. Samarakoon, P.D.S. Fernando, B.A.N. Mendis, R.P.P. Kanchana, G.W.D.A. Gunarathne, L.O. Ruggahakotuwa |
10.5120/ijca2022922367
|
H.M.U.S.S. Samarakoon, P.D.S. Fernando, B.A.N. Mendis, R.P.P. Kanchana, G.W.D.A. Gunarathne, L.O. Ruggahakotuwa . Automated Cancer Detection using Machine Learning and Image Processing. International Journal of Computer Applications. 184, 30 ( Oct 2022), 27-32. DOI=10.5120/ijca2022922367
Abstract
Cancer is becoming more prevalent around the globe. Even in Sri Lanka, the total cancer rate has doubled in the last 20 years, with a corresponding increase in cancer-related deaths. Cancer is the second leading cause of hospital death. Therefore, a solution to the problem should be an arrangement to reduce time waste, a correct method of directing the patient to detect symptoms, with highly accurate cancer detection, and a better monitoring system. The proposed system is an arrangement that permits and guides a patient to recognize symptoms on their own, directing them to an appropriate healthcare specialist, accurately detecting cancer in its initial stages and monitoring the patient throughout treatment. While cancer detection systems are analyzed, the existing research studies only use one machine learning methodology at a time to diagnose cancer. In the proposed work, Convolutional Neural Network (CNN), Random Forest and XGB Classifier are applied in detecting the presence of breast cancer, brain tumor, skin cancer and lung cancer which outputs results faster with a higher accuracy. This proposed system will be published as a modern cloud-based application which provides better user-experience and ease-of-use.
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