> For the complete documentation index, see [llms.txt](https://docs.flock.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.flock.io/flock-use-cases/privacy-preserving-healthcare.md). # Privacy-preserving Healthcare Beyond our work in the Web3 ecosystem, FLock is equally relevant in the Web2 world, and our flagship collaboration with a leading British hospital affiliated with a Top UK university is an excellent testimony to this. One of the biggest challenges of building AI models in the healthcare sector is data sharing. Since healthcare data is private, sensitive, and heterogeneous, collecting sufficient data for modelling is exhausted, costly, and sometimes impossible. \ FLock’s groundbreaking approach in leveraging blockchain-enabled FL has proven to be effective in preserving data privacy while significantly improving prediction accuracy compared to traditional methods. This approach facilitates global collaboration, allowing healthcare institutions to contribute to model training without sharing sensitive healthcare data directly. Our work has been tested in blood glucose prediction as a pilot but can be readily extended to model other chronic diseases or address broader healthcare challenges. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.flock.io/flock-use-cases/privacy-preserving-healthcare.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.