> For the complete documentation index, see [llms.txt](https://prep.pathcheck.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://prep.pathcheck.org/privacy-preserved-ai-for-healthcare/federated-split-learning.md).

# Federated and Split Learning

![](/files/-MYPubB8PvUxU8Ou-gky)

The final technique is federated and split learning. Jane wants to understand which medical treatment for given comorbidity leads to a successful recovery.  John’s phone trains a local AI to see how his health status and medical treatment lead to some kind of recovery or hospitalization. Although this local AI will be noisy because it only has data from John. If every user starts calculating such local AI and transmits the local AI parameters to the server. The server can then create the master AI by averaging these multiple local AI parameters. 

As you can see, John did not upload his private health data or whether he recovered.

{% embed url="<http://splitlearning.mit.edu>" %}

{% embed url="<https://en.wikipedia.org/wiki/Federated_learning>" %}

**References**<br>

\[1] Vepakomma, Praneeth, et al. “NoPeek: Information Leakage Reduction to Share Activations in Distributed Deep Learning.” ArXiv:2008.09161 \[Cs, Stat], Aug. 2020. arXiv.org, <http://arxiv.org/abs/2008.09161>.


---

# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://prep.pathcheck.org/privacy-preserved-ai-for-healthcare/federated-split-learning.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.