Private and energy-efficient decision tree-based disease detection for resource-constrained medical users in mobile healthcare network

S Alex, KJ Dhanaraj, PP Deepthi - IEEE Access, 2022 - ieeexplore.ieee.org
In mobile healthcare networks (MHN), outsourced disease detection services demand the
privacy preservation of medical users and health service providers (health clouds). This …

[HTML][HTML] The Application of Artificial Intelligence in Atrial Fibrillation Patients: From Detection to Treatment

H Liang, H Zhang, J Wang, X Shao, S Wu… - Reviews in …, 2024 - imrpress.com
Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although the guidelines for
AF have been updated in recent years, its gradual onset and associated risk of stroke pose …

Efficient detection of cardiac abnormalities via a simplified score-based analysis of the ECG signal

S Dhar, A Chakraborty, D Sadhukhan, S Pal… - Journal of Ambient …, 2024 - Springer
Nowadays, automated analysis of the electrocardiogram (ECG) signal is a popular choice to
facilitates easy and expert-independent detection of lethal cardiovascular diseases (CVDs) …

Energy Efficient and Secure Neural Network–based Disease Detection Framework for Mobile Healthcare Network

S Alex, D KJ, D PP - ACM Transactions on Privacy and Security, 2023 - dl.acm.org
Adopting mobile healthcare network (MHN) services such as disease detection is fraught
with concerns about the security and privacy of the entities involved and the resource …

Privacy-Preserving and Energy-Saving Random Forest-Based Disease Detection Framework for Green Internet of Things in Mobile Healthcare Networks

S Alex, KJ Dhanaraj, PP Deepthi - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The privacy of medical data and resource restrictions in the Internet of Things (IoT) nodes
prohibit medical users from utilizing disease detection (DD) services offered by the health …