Indian Journal of Science and Technology
DOI: 10.17485/IJST/v16i47.2758
Year: 2023, Volume: 16, Issue: 47, Pages: 4612-4619
Original Article
Tukaram Navghare1*, Aniket Muley1, Vinayak Jadhav2
1School of Mathematical Sciences, Swami Ramanand Teerth Marathwada University, Nanded, 431606, Maharashtra, India
2Shivaji College, Udgir, 413517, Maharashtra, India
*Corresponding Author
Email: [email protected]
Received Date:01 November 2023, Accepted Date:22 November 2023, Published Date:30 December 2023
Objectives: Breast cancer is one of the most ubiquitous cancers among women in the world and early exploration of the disease can be lifesaving. Finding breast cancer at an early stage enables quicker initiation of treatment, thereby enhancing the prospects of a positive outcome. Our aim is to identify the deep learning neural network model to classify breast cancer patients. Here, secondary open source data is considered to classify malignant and benign patients suitably. Methods: Deep learning neural network model, Artificial Neural Network and simulation approach is used to identify the more precise model. Findings: It is observed that, our proposed neural network model specified 97.5% accuracy. Efficiency of the proposed model is evaluated with the performance measures viz., MSE, RMSE etc. Novelty: The results of the study obtained through the proposed model express the efficiency of the model itself and also the superiority is demonstrated by comparing it with SVM, ANN, linear regression, 3DCNN deep models and existing works using various case studies. In the future, this model can be applicable in similar studies and it will give better results.
Keywords: Deep learning, Artificial Neural Network, Breast cancer, Classification, Wisconsin data set
© 2023 Navghare et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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