Breast Cancer Classification Using Deep Learning

• 出版年: Revolutionizing Healthcare Through Artificial Intelligence and Internet of Things Applications
• 第一著者: 2-s2.0-85167737571
• フォーマット: Book chapter
• 言語: English
• 出版事項: IGI Global 2023
• オンライン･アクセス: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167737571&doi=10.4018%2f978-1-6684-5422-0.ch005&partnerID=40&md5=a727c7e8359dcf81127bb7edccc29b15

Breast cancer (breast carcinoma) is the most common type of cancer in women, and it is the most dangerous cancer, together with lung cancer. Early detection of this type of cancer is crucial to reduce the mortality rate since breast cancer is often treatable when it is diagnosed early. Cancer starts from a benign state, and without appropriate treatment at the early stages, it becomes malignant. A common way to detect breast cancer is histological biopsy evaluation. Deep learning, as one of the currently most popular computer science research trends, improves neural networks, which have more and deeper layers allowing higher abstraction levels and more accurate data analysis. AI and machine learning have gained a lot of popularity and acceptance in recent years. Here are the top path breaking applications of deep learning in healthcare. Although deep convolutional neural networks as a deep learning algorithm has recently achieved promising results in data analysis, the authors propose a new deep CNN architecture for the classification of breast tumours in ultrasound images. © 2023 by IGI Global. All rights reserved.