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ISSN 2063-5346
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AN EFFECTIVE APPROACH TO NOVEL CONVOLUTIONAL NEURAL NETWORK ALGORITHM COMPARED WITH WATERSHED TRANSFORM ALGORITHM IN BREAST CANCER USING PRECISION

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S. Vishnu, S. S. Arumugam
» doi: 10.31838/ecb/2023.12.sa1.398

Abstract

Aim: The Objective of the work is to predict the Accuracy of Breast Cancer Prediction Using a Novel Convolutional Neural Network (NCNN) Comparative with the Watershed Transform Algorithm (WTA). Material and Methods: Accuracy and Loss are performed with a dataset from the GitHub library. The total sample size is 48. The two groups Novel Convolutional Neural Network (N=24), Watershed Transform Algorithm (N=24) watershed transform algorithm (WTA) was proposed by predicting the accuracy (80.90%) of Breast Cancer Prediction compared with the Novel Convolutional Neural Network. Results: The Result proved that the watershed Transform algorithm with Better accuracy than the Convolutional Neural Network. The Novel Convolutional Neural Network appears significantly better than Watershed Transform Algorithm (p<0.05). Discussion and Conclusion: The Prediction of breast cancer is better in novel Convolutional neural networks when compared with the watershed transform algorithm (WTA).

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