3–4 Nov 2022
Max Planck Institute for Dynamics of Complex Technical Systems
Europe/Berlin timezone

cancelled - Breast Cancer Prediction using Machine Learning Algorithms - A Deep Learning Approach

3 Nov 2022, 16:45
30m
Main/groundfloor-V0.05/2+3 - Prigogine (Max Planck Institute for Dynamics of Complex Technical Systems)

Main/groundfloor-V0.05/2+3 - Prigogine

Max Planck Institute for Dynamics of Complex Technical Systems

Sandtorstr. 1 39106 Magdeburg
100
Talk

Speaker

Darlington S. David (Georgia Institute of Technology)

Description

Breast Cancer is the deadliest and commonly diagnosed cancer in women globally. Early diagnosis and treatment of breast cancer increases the chance of a five-year survival rate by 99%. Recent technological and computational advancement have led to the discovery of machine learning algorithms for the analysis of complex data. Machine learning algorithms have been widely applied for the analysis of breast
cancer data. In this paper, we propose to implement machine learning algorithms, using a deep learning approach, for automatic detection and prediction of breast cancer using mammogram images. To achieve this, we implement transfer learning on a deep learning algorithm called Convolutional Neural Network (CNN). Two datasets of breast cancer images are analyzed using three CNN models in existing deep
learning frameworks. The models perform a binary and multiclass classification task on the images. Experimental results showed that CNN models can accurately identify and predict breast cancer when provided with a large and balanced dataset.

Primary authors

Ms B. Massa Weeks (University of Liberia) Darlington S. David (Georgia Institute of Technology) Mr Elijah Deah (University of Liberia)

Presentation materials

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