GenHealth's API provides developers with access to a powerful healthcare predictive analytics model.

Request access and view our [generative AI api documentation](https://docs.genhealth.ai/)

This API serves as a gateway for application developers to harness the capabilities of our large medical model (LMM) and build innovative healthcare apps. The LMM is a highly flexible and versatile model that can be seamlessly integrated into existing workflows or used as a standalone solution for a wide range of healthcare use cases.

The GenHealth's API is currently in a private beta, and enables users to create custom patient histories and run inference by leveraging demographic data, ICD diagnosis codes, CPT procedure codes, time gap tokens, and NDC prescription medication codes. With the ability to customize patient histories, developers can input diverse medical data and generate a representation of a patient's health journey. This feature empowers developers to tailor their applications to specific patient populations and medical scenarios.

Once a patient history is submitted to our api, you get a response with a generated set of simulated patient futures. These simulated futures provide predictions of potential medical events that a patient may experience based on their history. Developers can utilize these predictions to gain insights into possible health outcomes and make informed decisions regarding patient care and treatment plans.

In addition to the inference API, GenHealth's API provides the Inference API, which is currently in private beta. This API enables developers to programmatically access the predictive analytics capabilities of the LMM. By sending a request to the API with a patient's history, developers can receive predictions of future medical events, demographics, and meta tokens. This empowers developers to incorporate predictive analytics into their applications and provide personalized healthcare insights to their users.

For developers seeking to leverage the power of embeddings in their applications, GenHealth's API also offers the Embeddings API. This API allows developers to generate embeddings, which are vector representations, for any sequence or history of data. These embeddings can be used for various purposes such as semantic search, training classifiers, or other use cases that require understanding the contextual relationships between different data points. With the Embeddings API, developers can enhance the intelligence and functionality of their healthcare applications.

For more detailed information on these APIs and how to integrate them into your applications, please refer to the GenHealth documentation.