Learning Techniquesforpre-Malignancy Detection in Human Cells a Review
Gauraw F. Jumnake1, Parikshit N. Mahalle2, Gitanjali R. Shinde3
1Mr. Gauraw F Jumnake*, Research scholar, Department of Computer Engg., SKNCOE, Wadgaon, Pune, India.
2Dr. Parikshit N Mahalle, Professor & Hod, Department of Computer Engg., SKNCOE, Wadgaon, Pune, India.
3Dr. Gitanjali R Shinde, Assistant Professor, Department of Computer Engg., SKNCOE, Wadgaon, Pune, India.
Manuscript received on August 07, 2020. | Revised Manuscript received on August 15, 2020. | Manuscript published on August 30, 2020. | PP: 555-561 | Volume-9 Issue-6, August 2020. | Retrieval Number: F1622089620/2020©BEIESP | DOI: 10.35940/ijeat.F1622.089620
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© 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: Cancer is uncontrolled cell growth which starts consuming cell nourishment and keeps on multiplying indefinably. There are 100 plus different types of cancers that may affect any part of the body. In the past 26 years, the cancer incidence rate has been changed drastically in India. To control it early-stage detection of cancer plays a very important role. Early-stage detection of cancer helps in better diagnosis will also lower the chances of dying due to this deadly disease. It will impact considerably on the patient’s recovery when it is more treatable. Early Cancer detection or premalignant disease detection in the human body is possible through screening tests. Several screening methods have been tested, applied and proven to be very much efficient in reducing death rate due to cancer. This paper survey’s how learning techniques can be efficiently applied, tested and showed promising results in early-stage cancer detection through several screening methods.
Keywords: Cancer, Early Detection, Machine Learning, Screening Methods, Statistics