Breast Cancer Detection using Deep Learning

Breast Cancer Detection using Deep Learning

Mr. NOOR AHAMED J1 M.C.A., M.Phil.,, Mythili K2

1Assistant Professor(SG) , Department of Computer Applications, Nehru college of management, Coimbatore, Tamilnadu, India.

jnamca@gmail.com

2 II MCA, Department of Computer Applications, Nehru college of management, Coimbatore, Tamilnadu, India.

Abstract: One of the most researched issues in the medical field is the diagnosis of breast cancer. Numerous studies have been conducted on cancer diagnosis, highlighting the necessity of early cancer illness prediction. Health records are used as input to an automated system in order to provide advance prediction. The main goal of the paper is to build an automated system using recurrent neural network models based on deep learning. This research proposes an LSTM-BRNN-GRU that uses a patient's medical records to assess the likelihood that the patient will get breast cancer. The suggested model is contrasted with different baseline classifiers, including the RNN, LSTM, and GRU models. According to the study's comparative findings, the LSTM-BRNN-GRU model performs better in classification for breast cancer predictions.

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Keywords: Breast cancer, long short-term memory (LSTM), bidirectional recurrent neural network (BRNN), gated recurrent unit (GRU), predictive model, mammography.