An Analysis of Machine Learning and Deep Learning to Predict Breast Cancer

Title

An Analysis of Machine Learning and Deep Learning to Predict Breast Cancer

Creator

Raghuthaman A.; Jacob L.

Description

According to the report published by American Cancer Society, breast cancer is currently the most prevalent cancer in women. In addition, it is the second leading cause of death. It needs to be taken into serious consideration. Earlier and faster detection can help in the earlier and easier cure. Normally, medical practitioners take a large amount of time to understand and identify the presence of cancer cells in the human body. This can lead to serious complications even to the death of the individual. Hence there is a need to identify and detect the presence of this disease very accurately and in a shorter span of time. Like every other industry, the medical industry is shifting its paradigm to automation giving excellent results having high accuracy and efficiency, which is achieved using Artificial Intelligence. There are two sets of models developed based on the numerical dataset Wisconsin and image dataset BreakHis. Machine Learning algorithms and Deep Learning algorithms were applied on the Wisconsin dataset. Meanwhile, Deep Learning models were used for analysis of the Breakhis dataset. Machine Learning models- Logistic Regression, K Neighbors, Naive Bayes, Decision tree, Random Forest and Support vector classifiers were used. Deep Learning models- normal deep learning models, Convolutional Neural Network (CNN), VGG16 & VGG19 models. All the models have provided a very good accuracy ranging between 75% and 100%. Since medical research has a requirement for higher accuracy, these models can be considered and embedded into several applications. Grenze Scientific Society, 2022.

Source

13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022, Vol-8, pp. 695-703.

Date

2022-01-01

Publisher

Grenze Scientific Society

Subject

Accuracy; Breakhis; Breast Cancer; Classifier; Deep Learning; Machine Learning; WBCD; Wisconsin

Coverage

Raghuthaman A., Christ (Deemed to be University, Pune Lavasa Campus, Maharashtra, India; Jacob L., Christ (Deemed to be University, Pune Lavasa Campus, Maharashtra, India

Rights

Restricted Access

Relation

ISBN: 978-171385793-8

Format

Online

Language

English

Type

Conference paper

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143340610&partnerID=40&md5=62622698cc37d4d6575a057dd1b31148