@article{2791,
  keywords = {Blockchain, Health, Data Security, Data Privacy, Artificial Intelligence, Interoperability, Traceability},
  author = {H. S. Jennath and V S Anoop and S Asharaf},
  title = {Blockchain for Healthcare: Securing Patient Data and Enabling Trusted Artificial Intelligence},
  abstract = {Advances in information technology are digitizing the healthcare domain with the aim of improved medical services, diagnostics, continuous monitoring using wearables, etc., at reduced costs. This digitization improves the ease of computation, storage and access of medical records which enables better treatment experiences for patients. However, it comes with a risk of cyber attacks and security and privacy concerns on this digital data. In this work, we propose a Blockchain based solution for healthcare records to address the security and privacy concerns which are currently not present in existing e-Health systems. This work also explores the potential of building trusted Artificial Intelligence models over Blockchain in e-Health, where a transparent platform for consent-based data sharing is designed. Provenance of the consent of individuals and traceability of data sources used for building and training the AI model is captured in an immutable distributed data store. The audit trail of the data access captured using Blockchain provides the data owner to understand the exposure of the data. It also helps the user to understand the revenue models that could be built on top of this framework for commercial data sharing to build trusted AI models.},
  year = {2020},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {6},
  number = {3},
  pages = {15-23},
  month = {09/2020},
  issn = {1989-1660},
  url = {https://www.ijimai.org/journal/sites/default/files/2020-08/ijimai_6_3_2.pdf},
  doi = {10.9781/ijimai.2020.07.002},
}