What is Text Analytics for health in Azure Cognitive Service for Language?

Important

Text Analytics for health is a capability provided “AS IS” and “WITH ALL FAULTS.” Text Analytics for health is not intended or made available for use as a medical device, clinical support, diagnostic tool, or other technology intended to be used in the diagnosis, cure, mitigation, treatment, or prevention of disease or other conditions, and no license or right is granted by Microsoft to use this capability for such purposes. This capability is not designed or intended to be implemented or deployed as a substitute for professional medical advice or healthcare opinion, diagnosis, treatment, or the clinical judgment of a healthcare professional, and should not be used as such. The customer is solely responsible for any use of Text Analytics for health. The customer must separately license any and all source vocabularies it intends to use under the terms set for that UMLS Metathesaurus License Agreement Appendix or any future equivalent link. The customer is responsible for ensuring compliance with those license terms, including any geographic or other applicable restrictions.

Text Analytics for health is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language.

Text Analytics for health extracts and labels relevant medical information from unstructured texts such as doctor's notes, discharge summaries, clinical documents, and electronic health records.

This documentation contains the following types of articles:

  • Quickstarts are getting-started instructions to guide you through making requests to the service.
  • How-to guides contain instructions for using the service in more specific or customized ways.
  • The conceptual articles provide in-depth explanations of the service's functionality and features.

Features

Named Entity Recognition detects words and phrases mentioned in unstructured text that can be associated with one or more semantic types, such as diagnosis, medication name, symptom/sign, or age.

Text Analytics for health NER

Typical workflow

To use this feature, you submit data for analysis and handle the API output in your application. Analysis is performed as-is, with no additional customization to the model used on your data.

  1. Create an Azure Language resource, which grants you access to the features offered by Azure Cognitive Service for Language. It will generate a password (called a key) and an endpoint URL that you'll use to authenticate API requests.

  2. Create a request using either the REST API or the client library for C#, Java, JavaScript, and Python. You can also send asynchronous calls with a batch request to combine API requests for multiple features into a single call.

  3. Send the request containing your data as raw unstructured text. Your key and endpoint will be used for authentication.

  4. Stream or store the response locally.

Deploy on premises using Docker containers

Use the available Docker container to deploy this feature on-premises. These docker containers enable you to bring the service closer to your data for compliance, security, or other operational reasons.

Responsible AI

An AI system includes not only the technology, but also the people who will use it, the people who will be affected by it, and the environment in which it is deployed. Read the transparency note for Text Analytics for health to learn about responsible AI use and deployment in your systems. You can also see the following articles for more information:

Next steps

There are two ways to get started using the entity linking feature:

  • Language Studio, which is a web-based platform that enables you to try several Azure Cognitive Service for Language features without needing to write code.
  • The quickstart article for instructions on making requests to the service using the REST API and client library SDK.