Announcing ICD-10-CM and RxNorm Ontology Linking for Amazon Comprehend Medical
Medical ontologies, such as ICD-10, make it possible to classify unstructured medical information into standardized codes that downstream healthcare applications, such as revenue cycle management tools (medical coding) can read. Amazon Comprehend Medical ICD-10-CM RXNorm Ontology Linking extracts medical condition and medication entities from medical text and links them to the relevant ICD-10-CM and RXNorm concepts respectively.
Medical ontologies, such as ICD-10, make it possible to classify unstructured medical information into standardized codes that downstream healthcare applications, such as revenue cycle management tools (medical coding) can read. Amazon Comprehend Medical ICD-10-CM RXNorm Ontology Linking extracts medical condition and medication entities from medical text and links them to the relevant ICD-10-CM and RXNorm concepts respectively.
Using Amazon Comprehend Medical ICD-10-CM and RXNorm Ontology Linking APIs, developers can quickly and accurately extract codes (e.g. “R51” as the ICD-10-CM code for headache) from a variety of data sources, such as doctor’s notes or patient health records. Our deep learning approach to ontology linking provides much higher accuracy than existing rules-based systems by understanding the context each entity is found in.
Developers can use the linked ICD-10-CM and RXNorm concepts to build applications for use cases like revenue cycle management (medical coding) or population health management. ICD-10-CM and RXNorm Ontology Linking is available through simple API calls, no machine learning expertise required.
Visit the Amazon Comprehend Medical page to learn more, and check out this launch blog post.