Abstract
Significant and radical improvements in the healthcare industry today have facilitated the monitoring of patients through the internet. Breast cancer has become a widespread malaise across the globe, with many dependent on the internet for a diagnosis. A range of emerging technologies such as artificial intelligence, cloud computing and big data have been adopted in cancer diagnosis. Of late, a new framework for a cloud-based, multi-agent system to support secure intelligent mammogram image diagnosis for breast cancer detection has been developed. There is, as yet, not fully automated, generic, multi-agent intervention system with a cloud infrastructure for breast cancer patients, and implementation guidelines are, at best, deficient. The objective of this study is to enhance diagnostic performance, and increase scalability, response time and throughput. It is found that it has a high ratio of acceptance from users and attains superior sensitivity of up to 99.25% and accuracy of up to 99.0%.