An Intellectual Hybrid Machine Learning Model for Effective Breast Cancer Diagnosis-Reference-Cited by-同舟云学术

An Intellectual Hybrid Machine Learning Model for Effective Breast Cancer Diagnosis

Published:2024-04-22 Issue: Volume: Page:
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Author:

Nallamala Sri Hari¹,Mishra Pragnyaban²,Koneru Suvarna Vani³,Chakrabarti Prasun⁴,Chakrabarti Tulika⁴,Shanmuganathan Vimal⁵,Margala Martin⁶

Affiliation:

1. Vasireddy Venkatadri

2. GITAM University

3. V.R. Siddhartha Engineering College

4. Sir Padampat Singhania University

5. Ramco Institute of Technology

6. University of Louisiana at Lafayette

Abstract

Cancer was characterized as an illness brought about by an uncontrolled division of irregular cells in a piece of the body. Breast Cancer is characterized as a harmful development or tumor coming about because of an uncontrolled division of cells in the breast. Breast cancer is one of the most dangerous types of cancer after the lung cancer. The breast cancer is also considering as critical one like as skin cancer. Since, decades, women are suffering due to this breast cancer and also most of times majority percentage of them are dying due to non-identification at early stages and with the severity of the disease. Therefore, most of the doctors, scientists, researchers are did a major research and contributed for diagnosing the breast cancer at early stages and also curing process of the breast cancer. Here, in our research, we are also going to be diagnosing the breast cancer at early stages with the available less symptoms or data sets in an effective way to serve the needy people and finally trying to decrease the mortality rate by recovering them from the breast cancer. In this work, we have taken the most popular breast cancer datasets, i.e. Wisconsin Breast Cancer Datasets (i.e. Original and Diagnostic) as input to our proposed classifier to obtain the effective accuracy of classification which are nearly 98.97% and 97.73% respectively.

Publisher

Springer Science and Business Media LLC

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