Popular Medical API for web applications normal

   Published: 12 Nov 2024
We will provide you with your unique AuthenticationID value after you made a production order registration.

First request
The most important part of the API, which handles medical diagnostics, is the /api/DDxItems/ endpoint, which accepts POST requests. You will need to add AuthenticationID header to every request you make. Setup
The current version of the Diagnosis API is available at https://diagnosisapi.azurewebsites.net. It is a standard web service (Web API) that accepts GET and POST requests. All responses (including error messages) use the JSON format. Apart from laboratory test results, it requires a list of observed symptoms. POST requests also take JSON inputs (make sure you include the header Content-Type: application/json).
The Diagnosis API uses custom HTTP header to authenticate your requests. The lists cannot be empty, so first you need to collect an initial information to run diagnosis.For your Demo Development you can use AuthenticationID = DEMO_AuthenticationID.

Often powered by AI, it analyzes patient data inputs (like demographics, symptoms, and lab tests) or automatically extracts clinical features from electronic health records. This is an overview of available diagnosis API along with their primary use cases. Typically, diagnosis API includes two major components.
A knowledge base. The content is constantly reviewed and updated by medical professionals.
A diagnostic engine. How do healthcare organizations quickly implement such tools in their daily practice? The answer is clear and short - via APIs (application programming interfaces). But first, let's examine the main parts and core functionality of diagnosis API that can be integrated into a hospital's daily workflow.
DDxHub API is not here to put real physicians out of work. It contains data on conditions, diseases, and treatment procedures. Their mission is to keep patients better informed about the possible roots of their conditions and provide clinicians with decision support. The engine links patient information with pieces of content in the knowledge base and returns a list of likely conditions (preliminary diagnosis), care suggestions (triage), or both.