Early prediction and analysis of mammary glands cancer through deep learning approaches
Azteca University (Universidad Azteca), Department of Computer Science, Main Campus: 3 de Mayo, San Sebastián, Chalco Edo. de México.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2022, 06(01), 018–024.
Article DOI: 10.30574/wjaets.2022.6.1.0056
Publication history:
Received on 28 March 2022; revised on 10 May 2022; accepted on 12 May 2022
Abstract:
Cancer is the foremost cause behind the most death pace of people around the world. Cancer of breast is the primary reason for mortality among females. There have been various investigation or experimentation aimed at the discovery and interpretation of facts has been done on early expectation and discovery of breast cancer disease to begin treatment and increment the opportunity of endurance. Utmost research targets x-ray pictures of the breasts. Although, photographs of the breasts made by X-rays occasionally produces a threat of fake recognition which can compromise the medical status of infectious person. It’s crucial and import to locate opportunity techniques that might be simpler to put into effect and work with extraordinary records sets, inexpensive and safer, which could produce an extra dependable prognosis. This research journal recommends an associated prototype of numerous DLA (Deep Learning Algorithms) including ANN (Artificial Neural Network) and CNN (Convolutional Neural Networks) for efficient breast cancer detection and prediction. The research exploration utilizes the x-rays image database (as base research datasets) for prediction, detection, and diagnosis of breast cancer. This anticipated research prototype may be associated with several clinical examination data i.e. text, audio, image, video, blood, urine and many more.
Keywords:
Deep Learning; Chest Cancer; Prediction; ANN; CNN; AI
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Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0