Federated – Ensemble Learning (FEL) Techniques on Healthcare Data Privacy: A Review
Journal Title: International Journal for Modern Trends in Science and Technology - Year 2024, Vol 10, Issue 9
Abstract
In the realm of healthcare, protecting patient privacy by harnessing extensive medical data for enhanced clinical outcomes presents a significant challenge. Federated learning (FL) offers a promising solution by enabling collaborative model training without sharing sensitive data. This paper introduces the Privacy-Focused Ensemble Training (PFET) model within the framework of federated ensemble learning (FEL) to bolster data privacy and model performance in hospital environments. The PFET model integrates multiple local models trained independently across different hospitals into a cohesive global model, ensuring patient data remains secure and confined within each institution. Through extensive experiments on diverse medical datasets, our results show that the PFET model in FEL not only achieves high accuracy but also significantly reduces privacy risks compared to traditional centralized approaches. This innovative methodology has the potential to transform privacy-preserving data analysis in healthcare, promoting secure inter-institutional collaboration while safeguarding patient confidentiality.
Authors and Affiliations
Zainab Mukhtar Sani, Ajay Singh Dhabariya, Bachcha Lal Pal, Ahmad Umar Labdo, Jamilu Habu, Babangida S. Imam and Babangida Salisu Muazu
Keywords
Related Articles
- EP ID EP747907
- DOI https://doi.org/10.46501/IJMTST1009024
- Views 62
- Downloads 0
Improving AGC Performance in Two-Area Power Systems by Harnessing ANFIS Controller and Renewable Energy Source Integration
In modern power systems, maintaining stability and optimal performance amidst increasing demand and renewable energy integration presents significant challenges. This study explores the enhancement of Automatic Generatio...
Federated – Ensemble Learning (FEL) Techniques on Healthcare Data Privacy: A Review
In the realm of healthcare, protecting patient privacy by harnessing extensive medical data for enhanced clinical outcomes presents a significant challenge. Federated learning (FL) offers a promising solution by enabling...
Predicting Autism Spectrum Disorders Through Machine Learning Techniques
These days, autism spectrum disorder complaint is getting a wider issue affecting people of all periods. The conservation of the case's physical and internal health can be mainly backed by early opinion of this neurologi...
Formulation and quality characterization of soy milk based dietary ice cream with the incorporation of probiotics and utilization, of fruit waste as a functional ingredient
Ice cream production is a complex process involving various stages such as pasteurization, homogenization, aging, freezing, and packaging. The quality and characteristics of ice cream depend on several factors including...
Attendance Alerts – Timely Notifications for Late Arrivals
The Attendance Alert system is an advanced attendance management solution designed to streamline and enhance the efficiency and educational institutions. Leveraging facial recognition technology, this system automates th...