  Healthcare systems are increasingly incorporating Artificial Intelligence
into their systems, but it is not a solution for all difficulties. AI's
extraordinary potential is being held back by challenges such as a lack of
medical datasets for training AI models, adversarial attacks, and a lack of
trust due to its black box working style. We explored how blockchain technology
can improve the reliability and trustworthiness of AI-based healthcare. This
paper has conducted a Systematic Literature Review to explore the
state-of-the-art research studies conducted in healthcare applications
developed with different AI techniques and Blockchain Technology. This
systematic literature review proceeds with three different paths as natural
language processing-based healthcare systems, computer vision-based healthcare
systems and acoustic AI-based healthcare systems. We found that 1) Defence
techniques for adversarial attacks on AI are available for specific kind of
attacks and even adversarial training is AI based technique which in further
prone to different attacks. 2) Blockchain can address security and privacy
issues in healthcare fraternity. 3) Medical data verification and user
provenance can be enabled with Blockchain. 4) Blockchain can protect
distributed learning on heterogeneous medical data. 5) The issues like single
point of failure, non-transparency in healthcare systems can be resolved with
Blockchain. Nevertheless, it has been identified that research is at the
initial stage. As a result, we have synthesized a conceptual framework using
Blockchain Technology for AI-based healthcare applications that considers the
needs of each NLP, Computer Vision, and Acoustic AI application. A global
solution for all sort of adversarial attacks on AI based healthcare. However,
this technique has significant limits and challenges that need to be addressed
in future studies.
