Abstract
Blockchain has penetrated numerous domains such as, industries, government agencies, online voting, and healthcare, etc. Among these domains, healthcare is one of the trending and most important one, which consists of a control system and an Electronic Health Records (EHRs). Diabetes is one of the most rapidly growing chronic diseases that increases the death ratio across the globe. This paper presents a Blockchain-enabled diabetes disease detection framework that provides an earlier detection of this disease by using various machine learning classification algorithms and maintains the EHRs of the patients in a secure manner. Our EHRs sharing framework combines symptom-based disease prediction, Blockchain, and interplanetary file system (IPFS) in which the patient's health information are collected via wearable sensor devices. This information is then sent to EHRs manager, where an ML model is executed for further processing to collect the desired results. The results along with the physiological parameters are then stored in the Blockchain with the approval of concerned patient and his/her practitioner. It is anticipated that our proposed system will help the healthcare society in order to store, process, and share the patient health information in a secure manner.