Optimized Multi-Agent Deep Learning Framework for Lung Cancer Image Retrieval Using Medical Imaging Data

Abstract

The​‍​‌‍​‍‌​‍​‌‍​‍‌ rapid evolution of digital healthcare platforms has raised the need for secure and smart methods that can protect patient data while maintaining accurate disease prediction. The present study offers a futuristic e-healthcare system entitled Optimized Multi-Agent Deep Learning Framework for Lung Cancer Image Retrieval Using Medical Imaging Data. The circulated copy intends to focus on the prediction as well as the detection of lung diseases by utilizing machine learning (ML) and deep learning (DL) models to attain high diagnostic accuracy. A web-based front end has been created using the Django framework to facilitate easy user access to predictions and medical insights. In an attempt to preserve the privacy and security of sensitive health records, blockchain technology has been merged for data storage that is decentralized and tamper-proof. Besides that, multi-agent-based privacy metrics have been activated to keep track of, study, and raise the privacy levels through the system, thus providing an adaptive shield against the leakage of data and unauthorized access. The suggested scheme enhances the security of data privacy and at the same time raises the level of trust, transparency, and efficiency in digital healthcare applications. Such a combined system is an excellent example of how healthcare services can be revolutionized by the union of AI-powered disease detection and privacy-preserving ​‍​‌‍​‍‌​‍​‌‍​‍‌methods.