Machine Learning Based Approach for Breast Cancer Detection
Harshita Suresh Hegde, Ashwini Kodipalli · 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · 2022
Breast cancer is one of the deadliest diseases faced by many women in the world. This cancer is more common in women than men. Breast cancer is the 2nddangerous cancer suffered by women in the world. The mortality rate is very high. 2.3 million women already in the list of diagnosed with breast cancer and death rate is also increased by 685 000 deaths throughout world according to the reports published in 2020 by WHO. Over past 5 years it is observed that a huge number breast cancer affected women are predicted of about 7.8 million. Hence it is a genuine issue for the women and their health. This cancer can’t be cure at final stage. But the cancer normally predicted at 2ndor 3rdstage by physicians. It is better when recognized it at an early stage. Due to advancement in computational algorithms, there is a possibility of prediction model of breast cancer. This work is mainly focusing on developing prediction of breast cancer using classification algorithms. Among all the classification algorithm used such as K NN, Logistic Regression, Naive Bayes, SVM, Decision Tress and Random Forest. Logistic Regression has outperformed with the 98.74%.