Privacy-Protected Data Mining and CNN for E-Healthcare Systems

The E-Health care system is crucial in modern health care. These systems are designed to secure medical data repositories. The main goal of this study is to ensure both security and privacy by enhancing fully homomorphic data collection. It also aims to improve classification accuracy in disease detection. The existing method of Privacy-Preserving Data Mining (PPDM) is utilized to maintain privacy in healthcare, and the new method using a Convolutional Neural Network (CNN) algorithm is employed to identify diseases more accurately. This new approach enhances performance by achieving higher accuracy, recall, and reducing time complexity.