API

Text Analytics for health

Unlock meaningful insights from unstructured healthcare text data.

Microsoft’s Text Analytics for health is a cloud-based API service that applies machine-learning intelligence to convert unstructured healthcare data into structured healthcare data to enable further processing. It performs 4 key functions in a single API call:

  • Named Entity Recognition — extracts and categorizes words and phrases
  • Relation Extraction — identifies meaningful connections between concepts
  • Entity Linking — associates extracted entities with preferred names and codes from the biomedical vocabularies supported by EMLA Metathesaurus
  • Assertion Detection — adds contextual certainty, conditional, association, and temporal modifiers to words and phrases

Microsoft Text Analytics for health is a third-party product: By requesting information, you consent to your information being shared with Microsoft.

Develop predictive models and assist with decision support

Power solutions for planning, decision support, risk analysis and more, based on prediction models created from historic data. Assist clinicians in making faster and more reliable decisions with extracted patient medical record data.

Help enforce medical accuracy

Annotate, curate, review and report medical information to report and flag possible errors in medical information resulting from review processes such as quality assurance.

Accelerate time to healthcare insights

Analyze large volumes of data from clinical and scholarly sources to predict health trends and prepare for future challenges.

Developer resources

Text Analytics for Health

API Quickstart
Related resources
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Video

Help speed claim processing with prescription text analysis

Text Analytics for health identifies, labels, and associates key medical information in prescription text to help reduce transaction costs and enable faster payments

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Video

Facilitate easier diagnosis and analysis

Text Analytics for health extracts critical and relevant medical information from unstructured data to support better healthcare management and patient care,

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Learning module

Gain insight from unstructured health data

By analyzing unstructured text data, Text Analytics for health can help advance patient disease diagnosis and condition assessment, clinical trial matching, and nurse care delivery.

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Frequently Asked Questions

Can I use Text Analytics for health while I wait for it to become available on Optum Marketplace?

Yes! If you are an Azure customer you can test out a demo by following these instructions

What are the key features of Text Analytics for health?

Text Analytics for health is one of the prebuilt features offered by Azure AI Language. It is a cloud-based API service that applies machine-learning intelligence to extract and label relevant medical information from a variety of unstructured texts such as doctor's notes, discharge summaries, clinical documents and electronic health records.

It can perform:

  1. Named entity recognition
  2. Relation extraction
  3. Entity linking
  4. Assertion detection

Do I need an Azure subscription to use Text Analytics for health?

No. It is hosted on your behalf under the Optum Azure subscription.

How can I integrate it with my existing healthcare systems?

Text Analytics for health can output .json-formatted documents or FHIR format.

What types of data can be processed?

Text Analytics for health processes unstructured clinical, medical, or healthcare-related texts such as doctors' notes, discharge summaries, clinical documents, and electronic health records. It converts this unstructured data into structured data for further processing.

How does Text Analytics for health ensure data privacy and security?

Data, privacy, and security for Azure AI Language services, including Text Analytics for health, can be found on Microsoft's website. 

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