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articles/ai-services/language-service/personally-identifiable-information/overview.md

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PII detection is one of the features offered by [Azure AI Language](../overview.md), a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The PII detection feature can **identify, categorize, and redact** sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Azure AI Language supports general text PII redaction, as well as [Conversational PII](how-to-call-for-conversations.md), a specialized model for handling speech transcriptions and the more informal, conversational tone of meeting and call transcripts. The service also supports [Native Document PII redaction](#native-document-support), where the input and output are structured document files.
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> [!TIP]
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> PII detection is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](https://learn.microsoft.com/azure/ai-studio/ai-services/connect-ai-services) in order to use this service.
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> PII detection is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](../../../ai-studio/ai-services/connect-ai-services.md)
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* [**Quickstarts**](quickstart.md) are getting-started instructions to guide you through making requests to the service.
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* [**How-to guides**](how-to-call.md) contain instructions for using the service in more specific or customized ways.

articles/ai-services/language-service/summarization/overview.md

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Out of the box, the service provides summarization solutions for three types of genre, plain texts, conversations, and native documents. Text summarization only accepts plain text blocks, and conversation summarization accept conversational input, including various speech audio signals in order for the model to effectively segment and summarize, and native document can directly summarize for documents in their native formats, such as Words, PDF, etc.
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> [!TIP]
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> Summarization is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](https://learn.microsoft.com/azure/ai-studio/ai-services/connect-ai-services) in order to use this service.
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> Summarization is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](../../../ai-studio/ai-services/connect-ai-services.md) in order to use this service.
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# [Text summarization](#tab/text-summarization)
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articles/ai-services/language-service/text-analytics-for-health/overview.md

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Text Analytics for health is one of the prebuilt features offered by [Azure AI Language](../overview.md). 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.
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> Text Analytics for health is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](https://learn.microsoft.com/azure/ai-studio/ai-services/connect-ai-services) in order to use this service.
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> Text Analytics for health is also [available in AI Studio](https://ai.azure.com/explore/language), where you can [utilize a currently existing Language Studio resource or create a new AI Studio resource](../../../ai-studio/ai-services/connect-ai-services.md) in order to use this service.
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This documentation contains the following types of articles:
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* The [**quickstart article**](quickstart.md) provides a short tutorial that guides you with making your first request to the service.

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