Breast Tumor Classification using Machine Learning: Breast Tumor Classification using Machine Learning

Salman Siddiqui; Mohd Usman Mallick; Ankur Varshney

doi:10.4108/eetcasa.v9i1.3600

Authors

Salman Siddiqui Jamia Millia Islamia https://orcid.org/0000-0001-7209-1392
Mohd Usman Mallick Hindu Rao Hospital
Ankur Varshney Amdocs Development Center India

DOI:

https://doi.org/10.4108/eetcasa.v9i1.3600

Keywords:

Machine Learning, Tumor Classification, Accuracy, MCDM, Breast Cancer

Abstract

One of the most contagious illnesses and the second-leading cause of cancer-related death in women is breast cancer. Early detection of tumor is critical for providing healthcare providers with useful clinical information which can help them make a more accurate diagnosis. To accurately diagnose breast cancer, a computer-aided detection (CAD) system that employs machine learning is required. The paper proposes web based tumor prediction system which analyzes different machine learning algorithms for breast tumor classification to determine the best performing model. Different evaluation criteria namely accuracy, ROC AUC, etc are mostly employed for evaluating models but they make the selection of the best model strenuous. A multi-criteria decision making (MCDM) approach has been employed for selecting the best performing model. Further, a web-based portal has been developed to provide the user interface for this functionality.

Author Biographies

Mohd Usman Mallick, Hindu Rao Hospital

NDMC Medical College

Ankur Varshney, Amdocs Development Center India

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