Confluence of Blockchain and Artificial Intelligence Technologies for Secure and Scalable Healthcare Solutions: A Review

Abstract

Blockchain (BC) and artificial intelligence (AI) technologies have independent applications in multiple industries, including banking, finance, healthcare, construction, transportation, hospitality, manufacturing, and insurance, to name a few. Moreover, these two technologies can be integrated seamlessly, thanks to their complementary and mutually supportive features. AI algorithms can make the medical BC storage efficient by their processing algorithms, also playing the role of knowledgeable gatekeepers. BC can support AI models by providing secure, sizeable, traceable, diverse, and immutable healthcare data for the training purpose. The integration of BC and AI has multiple use cases in the healthcare industry ranging from disease prediction to pandemic management. Previously, researchers have reviewed the applications of each of these technologies in healthcare independently. Although the integration of BC and AI has been fruitful, to the best of our knowledge, there has been no work in the past reviewing the confluence of these two technologies in the healthcare sector. We have classified the works based on two different classification schemes: 1) application-based and 2) AI-training paradigm-based classification. We have also provided a compilation of tools used in the integrated systems of BC and AI for healthcare. We identified that the integration of BC and AI technologies had been applied in quite different areas of healthcare ranging from biomedical research to pandemic management. It is also noted that the supervised learning algorithms and federated learning paradigm for secure decentralized AI model training are often used in the integration. Our findings reveal that majority of the reviewed works use BC as a secure database for AI models. Furthermore, we also have pointed out the potential applications of these two technologies in healthcare.

Ähnliche Arbeiten