Current status of artificial intelligence and machine learning in breast cancer screening: A systematic review
1 Department of Internal Medicine, Community Hospital of San Bernardino, CA, USA.
2 Department of Internal Medicine, Ascension Via Christi Hospital, KS, USA.
3 Department of Internal Medicine, SSM St Mary’s Hospital, St Louis. MO, USA
4 Department of Internal Medicine, University of California Riverside, CA, USA.
5 Department of Internal Medicine, Trumbull Regional Medical Center, OH, USA.
6 Clinical Research Program, Rush University, IL, USA.
Review Article
Magna Scientia Advanced Research and Reviews, 2024, 11(01), 060–067
Article DOI: 10.30574/msarr.2024.11.1.0073
Publication history:
Received on 22 March 2024; revised on 02 May 2024; accepted on 04 May 2024
Abstract:
Breast cancer stands as one of the most prevalent forms of cancer. Artificial intelligence (AI) and machine learning have become crucial in accurately identifying and managing various serious illnesses. This development has contributed to improved survival rates by enabling early detection and timely intervention. In our investigation, we conducted a thorough systematic review of the role of AI and machine learning in breast cancer screening. We examined articles from 2015 to 2023 across diverse databases, focusing on the intersection of breast cancer and AI. The integration of AI into existing screening procedures yields more convenient and efficient outcomes. Utilizing AI techniques in breast cancer screening offers numerous benefits, including heightened precision in results. However, the incorporation of AI presents several challenges that need systematic addressing.
Keywords:
Breast Cancer; Artificial Intelligence; Machine Learning; Screening; AI; Challenges
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0