Amazon Comprehend Medical is a service that detects useful information in unstructured clinical text. As much as 75% of all health record data is found in unstructured text: physician’s notes, discharge summaries, test results, case notes, and so on. Amazon Comprehend Medical uses Natural Language Processing (NLP) models to sort through enormous quantities of data for valuable information gained through advances in machine learning.

Supported Languages

With this initial release, Amazon Comprehend Medical only detects medical entities in English language texts.

Important Notice

Amazon Comprehend Medical is not a substitute for professional medical advice, diagnosis, or treatment. Amazon Comprehend Medical provides confidence scores that indicate the level of confidence in the accuracy of the detected entities. Identify the right confidence threshold for your use case, and use high confidence thresholds in situations that require high accuracy. In certain use cases results should be reviewed and verified by appropriately trained human reviewers. For example, Amazon Comprehend Medical should only be used in patient care scenarios after review for accuracy and sound medical judgment by trained medical professionals.


The following examples show how you might use Amazon Comprehend Medical in your health care applications:

Example 1: Patient Case Management and Outcome

Doctors and health care providers can manage and easily access medical information that doesn’t easily fit into forms traditionally used. By analyzing case notes, providers can identify candidates for early screening of medical conditions before the condition becomes more difficult and expensive to treat. It allows patients to report their health concerns in a narrative that can provide more information than simple formats. The narratives are then easily available to providers, allowing more accurate diagnosis of medical conditions.

Example 2: Clinical Research

Life sciences and research organizations can:

  • Optimize the matching process for fitting patients into clinical trials using information from unstructured clinical texts, such as case notes and test results. For instance, for a clinical trial of a new heart medicine, it enables simple analysis of text for specific information about heart failure patients.
  • Improve pharmacovigilance and post-market surveillance to monitor adverse drug events by using Amazon Comprehend Medical to detect pertinent information in clinical text.
  • Assess therapeutic effectiveness by easily detecting vital information in follow-up notes and other clinical texts. For instance, it can be easier and more effective to monitor how patients respond to certain therapies by analyzing their narratives.

Example 3: Medical Billing and Healthcare Revenue Cycle Management

Payors can expand their analytics to include unstructured documents such as clinical notes, where more information about a diagnosis as it relates to billing codes can be determined. Natural language processing (NLP) is the most critical component of computer-assisted coding (CAC). Amazon Comprehend Medical uses the latest advances in NLP to analyze clinical text, helping to decrease time to revenue and improve reimbursement accuracy.


Some of the benefits of using Amazon Comprehend Medical include:

  • Integrate powerful natural language processing into your applications—Amazon Comprehend Medical uses a simple API to build text analysis capabilities into your applications for powerful and accurate natural language processing. You don’t need textual analysis expertise to take advantage of the insights that Amazon Comprehend Medical produces.
  • Deep learning based on natural language processing—Amazon Comprehend Medical uses deep learning technology to accurately analyze text. Our models are constantly trained with new data across multiple domains to improve accuracy.
  • Scalable natural language processing—Amazon Comprehend Medical enables you to detect the information from millions of documents, making more rapid insights into patient health and care possible.
  • Integrate with other AWS services—Amazon Comprehend Medical is designed to work seamlessly with other AWS services like Amazon S3 and AWS Lambda. Store your documents in Amazon S3, analyze real-time data with Kinesis Data Firehose, or use Amazon Transcribe to easily transcribe patient narratives into text that can be easily analyzed by Amazon Comprehend Medical. Support for AWS Identity and Access Management (IAM) makes it easy to securely control access to Amazon Comprehend Medical operations. Using IAM, you can create and manage AWS users and groups to grant the appropriate access to your developers and end users.
  • Low cost—With Amazon Comprehend Medical, you only pay for the documents that you analyze. There are no minimum fees or upfront commitments.

HIPAA compliance

This is a HIPAA Eligible Service. For more information about AWS, U.S. Health Insurance Portability and Accountability Act of 1996 (HIPAA), and using AWS services to process, store, and transmit protected health information (PHI), see HIPAA Overview.

Connections to Amazon Comprehend Medical containing PHI must be encrypted and, by default, all connections to Amazon Comprehend Medical use HTTPS over TLS. Amazon Comprehend Medical does not persistently store customer content and therefore does not require customers to configure encryption at-rest within the service.