A Blockchain-Assisted Adaptive Deep Learning and Swarm Intelligence Framework for Secure IoT-Enabled Smart Pathological Labs Real-Time Disease Detection

Background Information: The Internet of Things transforms pathological laboratories by facilitating real-time diagnosis and optimising resource management; nonetheless, issues such as security vulnerabilities and delays remain prevalent. Objectives: Construct a Blockchain-Enhanced Adaptive Deep Learning and Swarm Intelligence Framework for safe, real-time diagnostics and optimised Internet of Things healthcare systems. Methods: The platform incorporates blockchain for data protection, adaptive deep learning for accurate diagnosis, and swarm intelligence for resource distribution. Results: Attained 94.2% accuracy, 93.5% precision, 0.98 data security, 0.95 scalability, and decreased processing time to 110.7 ms. Conclusion: The platform provides secure, scalable, and efficient pathological laboratories, tackling IoT issues while facilitating real-time healthcare and enhanced operations.