ISSN: 1007-1172

Impact Factor: 6.2

UGC-CARE APPROVED MULTIDISCIPLINARY JOURNAL

Journal of Shanghai Jiaotong University

International Peer Reviewed | Open Access | A Monthly Publishing Journal

"A Study of Deep Learning techniques for predicting breast cancer types"

Authors

P.Ashwini, Assistant Professor
Department of Computer Science and Engineering,CVR College of Engineering, Hyderabad, India.

Dr.N.Suguna, Associate Professor
Department of Computer Science and Engineering,Annamalai University, Chidambaram, India.

Dr.Vadivelan N, Professor
Department of Computer Science and Engineering, Teegala Krishna Reddy Engineering College, Hyderabad, India.

Abstract

Breast Cancer is today’sdeadly health issue which causes high mortality in womanworldwide. Thepreliminary detection and classification may help for proper treatment of the same. Understanding the causes of this cancer usingtraditional Machine learning techniques misread feature extraction are leading to acomplication. The novel deep learning techniques have been introduced for diagnosis of breast abnormalitieswith high accuracy. This survey focuses on challenges of classicalmachine learning models and supervene efficient predictionmodels using novel deeplearning techniques. This review presents comparison of traditional machine learning and deep learning models