Intelligent, Secure Big Health Data Management Using Deep Learning and Blockchain Technology: An Overview

Abstract

Sensor-based health data collection, remote access to health data to render real-time advice have been the key advantages of smart and remote healthcare. Such health monitoring and support are getting immensely popular among both patients and doctors as it does not require physical movement which is always not possible for elderly people who lives mostly alone in current socio-economic situations. Healthcare Informatics plays a key role in such circumstances. The huge amount of raw data emanating from sensors needs to be processed applying machine learning and deep learning algorithms for useful information extraction to develop an intelligent knowledge base for providing an appropriate solution as and when required. The real challenge lies in data storage and retrieval preserving security, privacy, reliability and availability requirements. Health data saved in Electronic medical record (EMR) is generally saved in a client-server database where central coordinator does access control like create, access, update, or delete of health records. But in smart and remote healthcare supported by enabling technologies such as Sensors, Internet of Things (IoT), Cloud, Deep learning, Big data, etc. EMR needs to be accessed in a distributed manner among multiple stakeholders involved such as hospitals, doctors, research labs, patients’ relatives, insurance provider, etc. Hence, it is to be ensured that health data be protected from unauthorized access specifically to maintain data integrity using advanced distributed security techniques such as blockchain.