Machine Learning Application in Breast Cancer Detection and Diagnosis: A Comprehensive Review
Bersha Kumari, Amita Nandal, Arvind Dhaka · 2023
Breast cancer growth stays an inescapable and hazardous sickness influencing a huge number of women around the world. Opportune and exact analysis is vital for further developing endurance rates and fitting treatment methodologies. As of late, the mix of AI (ML) methods into Breast cancer growth discovery and determination has shown noteworthy commitment. This extensive survey investigates the complex job of ML in Breast cancer growth research, drawing experiences from key examinations and audits. We dig into the different uses of ML calculations, information sources, and modalities, accentuating their capability to improve indicative exactness, risk expectation, and customized treatment proposals. Moreover, we highlight the challenges and future directions in harnessing ML's transformative power to combat breast cancer effectively.