Efficient Management of Access Control Mechanism and BlockChain using Machine Learning in PHR

Health is one of the most integral parts of human life. Health has been one of the most widely researched topics ever since the dawn of mankind and it has been improved to a large degree through the implementation of the technological advancements made by humans. Technology has been utilized to make it easier for doctors to diagnose and treat a certain patient with the utmost accuracy and of the diagnosis. For this purpose, most of the developed nations utilize the Public Health Records or the PHR platform that records the medical history of the patient along with the various treatments offered to the patient. This helps streamline the approach and mitigate the effects of the disease. The problem arises when the patient goes to a new doctor or a medical institute, where his/her data is not present. For this purpose, the doctor is facilitated with the data vendors that provide the data to the doctor according to the parameters by the doctor. But due to the personal nature of the records and the lack of trust between the Data vendor and the data provider it becomes a difficult task. Therefore, the proposed methodology outlines an effective and secure approach towards the sharing of the PHR data through the utilization of the blockchain platform. The proposed methodology utilizes Linear clustering and Fuzzy Artificial Neural Networks along with the Distribution Factor Estimation for effective and secure implementation of the access control mechanism for the PHR Data.