Scopus Indexed Publications

Paper Details


Title
Breast Cancer Detection using Machine Learning Approach
Author
Rohena Begum Mim, Abdus Sattar, Afra Bente Islam, Sudipta Roy,
Email
rohena15-11388@diu.edu.bd.
Abstract

We have gathered the features of breast cancer and normal persons’ cells both. To classify malignant and benign tumors, we used a supervised machine learning classifier algorithm. This paper shows the last update in this machine learning field on breast cancer in Bangladesh. We have used many classifiers of ML in this review. Most of cases it is difficult to identify the malignant tumors. For this, we hoped that with the help of math and the computational power of ML we can resolve this issue at a significant scale. Yet, there were a few difficulties with the process. Starting with featuring the dataset and creating a data frame we proceed to apply different types of machine learning classifiers. This paper presents an overview of the opinion examination challenges applicable to their methodologies and strategies.

Keywords
Correlation , Machine learning algorithms , Malignant tumors , Null value , Benign tumors , Machine learning , Feature extraction
Journal or Conference Name
International Conference on Electrical, Computer, and Energy Technologies, ICECET 2022
Publication Year
2022
Indexing
scopus