What is Text Analytics for health in Azure Cognitive Service for Language?
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.
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.
Text Analytics for health features
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.
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.
Get started with Text analytics for health
To use this feature, you submit raw unstructured text 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. There are three ways to use Text Analytics for health:
|Language Studio||A web-based platform that enables you to try Text Analytics for health without needing writing code.||• Language Studio website
• Quickstart: Use the Language studio
|REST API or Client library (Azure SDK)||Integrate Text Analytics for health into your applications using the REST API, or the client library available in a variety of languages.||• Quickstart: Use Text Analytics for health|
|Docker container||Use the available Docker container to deploy this feature on-premises, letting you bring the service closer to your data for compliance, security, or other operational reasons.||• How to deploy on-premises|
Input requirements and service limits
- Text Analytics for health takes raw unstructured text for analysis. See Data and service limits for more information.
- Text Analytics for health works with a variety of written languages. See language support for more information.
Reference documentation and code samples
As you use Text Analytics for health in your applications, see the following reference documentation and samples for Azure Cognitive Services for Language:
|Development option / language||Reference documentation||Samples|
|REST API||REST API documentation|
|C#||C# documentation||C# samples|
|Java||Java documentation||Java Samples|
|Python||Python documentation||Python samples|
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:
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