Spinal PMDMNN: a new blockchain-based IOT network for healthcare classification
Yogesh R. Kulkarni, Shounak Rushikesh Sugave, Balaso N. Jagdale, Vitthal Sadashiv Gutte · Australian Journal of Electrical & Electronics Engineering · 2025
Medical care is emerged as the most important aspect of people’s lives. The health care providers are embracing Internet of Things (IoT)-based wearable approaches for assisting the diagnosis and treatment. In recent years, the IoT has provided billions of sensors and devices for disease detection and health condition monitoring. This paper developed a blockchain-based IoT model for privacy-preserving healthcare classification. The simulated model of the blockchain-enabled IoT provided the healthcare data. The fusion of medical data with a privacy matrix created the preserved data. Moreover, the privacy matrix generation is the process of creating the privacy matrix using the hybrid optimisation approach. For that, the proposed Aquila Hunter prey Optimisation (AHPO) is employed. The data augmentation process based on Over sampling process enhanced the size of the data. In the healthcare classification process, the proposed privacy matrix enabled Deep Maxout Network with SpinalNet (Spinal PMDMNN) is employed. The performance of the model is accessed using accuracy, True Positive Rate (TPR) and True Negative Rate (TNR), with the corresponding values 0.976, 0.947 and 0.925 are attained.