Title: A secure cloud-based multi-agent intelligent system for mammogram image diagnosis

Authors: S.R. Bhavani; A. Chilambuchelvan; J. Senthilkumar; D. Manjula; R. Krishnamoorthy; A. Kannan

Addresses: Department of Computer Science and Engineering, Anna University, Chennai, Tamil Nadu, India ' Department of Computer Science and Engineering, Anna University, Chennai, Tamil Nadu, India ' Department of Computer Science and Engineering, Anna University, Chennai, Tamil Nadu, India ' Department of Computer Science and Engineering, Anna University, Chennai, Tamil Nadu, India ' Department of Computer Science and Engineering, Bharathidasan Institute of Technology, Anna University - BIT Campus, Tiruchirapalli, Tamil Nadu, India ' Department of Information Science and Technology, College of Engineering, Anna University, Chennai, Tamil Nadu, India

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%.

Keywords: multi-agents; cloud computing; breast cancer; representative association rule; image diagnosis.

DOI: 10.1504/IJBET.2018.094726

International Journal of Biomedical Engineering and Technology, 2018 Vol.28 No.2, pp.185 - 202

Received: 18 Jul 2016
Accepted: 27 Sep 2016

Published online: 30 Aug 2018 *

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