Development of AI Models from Mammography Images with CNN for Early Detection of Breast Cancer

Nurbaiti Nurbaiti; Eka Putra Syarif Hidayat; Khairil Anwar; Dudung Hermawan; Salman Izzuddin

doi:10.29407/gj.v8i1.21601

Authors

Nurbaiti Nurbaiti Poltekkes Kemenkes Jakarta II
Eka Putra Syarif Hidayat Poltekkes Kemenkes Jakarta II
Khairil Anwar Poltekkes Kemenkes Jakarta II
Dudung Hermawan Universitas Islam Asy syafiiyah
Salman Izzuddin Universitas Mercu Buana

DOI:

https://doi.org/10.29407/gj.v8i1.21601

Keywords:

Breast Cancer, Early Detection, Artificial Intelligence, Convolutional Neural Network

Abstract

Early detection of breast cancer with computer assistance has developed since two decades ago. Artificial intelligence using the convolutional neural network (CNN) method has successfully predicted mammography images with a high level of accuracy similar to human brain learning. The potential of AI models provides opportunities to spot breast cancer cases better. This research aims to develop AI models with CNN using the public DDSM dataset with a sample size of 1871, consisting of 1546 images for training and 325 images for testing. These AI models provided prediction results with different accuracy rate. Increasing the accuracy of the AI model can be done by improving the image quality before the modeling process, increasing the number of datasets, or carrying out a more profound iteration process so that the AI model with CNN can have a better level of accuracy.

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