Detection of Cancer using Machine Learning Algorithms

Shelar Akshay Dilip

Abstract


Cancer is a group of diseases characterized by uncontrolled growth and spread of abnormal cells. There are over 100 types of cancer. And any part of the body can be affected. Cancer has become 2nd leading cause of death. Some hospitals offer cancer screening tests; the test results need to be evaluated by an oncologist. The cancer screening test are very expensive and not available in all of the hospital. The expensive nature of test causes economically weaker section to skip the routine check-ups, most privilege class people tends to skip the routine check-ups too due to scarcity of check-up facilities in their cities, villagers too are affected by these two causes. Early detection of cancer can help in eradicating the disease from patient, but if it is left unchecked and is discovered at critical stage, treatment of the disease is very difficult. Using advanced algorithms and harnessing full potential of machine learning, this screening test can be availed at all the hospitals and clinics and the system could predict the disease with a precision such that making oncologist’s intervention unneeded in most cases.


Keywords


Cancer, artificial intelligence, neural network, image processing, prediction, analysis, oncology, radiology, decision tree algorithm, fuzzy c-mean clustering algorithm, early detection

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DOI: https://doi.org/10.37591/tmd.v7i3.4956

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