Cancer prognosis & Survival rate prediction using machine learning algorithm.

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Department of Electronic and Telecommunication Engineering


Roughly 10 million deaths, or nearly one in six deaths, were caused by cancer in 2020, making it the top cause of death globally. Breast, lung, colon, rectum, and prostate cancers are the most prevalent types of cancer. Any disease that can affect any region of the body is referred to as cancer. Neoplasms and malignant tumors are other words that are used. One characteristic of cancer is the quick development of aberrant cells that expand outside of their normal borders, infiltrate other body components, and eventually move to other organs. This process is known as metastasis. The main reason why cancer patients die is because of widespread metastases [1]. The research was held on two different datasets of breast cancer. To train our model initially we used a primary data set from UCI which includes 569 instances with several attributes [2]. This was for cancer diagnosis prediction/detection. Then we used another dataset that includes 4024 instances with 14 different attributes which we mainly used for death rate prediction with total analysis [3]. Here 6 algorithms were incorporated including KNN, Random Forest, J48, etc., and their results were compared.


Submitted by Borhan Uddin Alif T181020


Cancer Diagnosis, Breast Cancer, KNN, Random Forest, Feature Selection