Federated Learning-Based Disease Diagnosis and Treatment Recommendation System Using Blockchain

Abstract

In the medical field, significant changes have been provided by advancements in technology. But, owing to the higher scalability of modern healthcare networks and growing data privacy concerns, centralized collection and processing of medical data are infeasible. Hence, this work proposes Federated Learning-based Disease Diagnosis and Treatment Recommendation System (FL-DDTRS) with blockchain. Primarily, from the patients with IoT devices, attributes are extracted, which are then fed into the local model named the Disease Diagnosis and Treatment Recommendation System (DD-TRS) system. DD-TRS data obtained from the patient’s discharge summary dataset is pre-processed and the medical term is identified