Extract information from clinical documents constantly and quickly


Unleashing the Potential of Unstructured Medical Text

Experience the power of SmartCare APIs, a developer-friendly, clinical natural language processing (cNLP) service. Unlocking health data from clinical narrative text has never been easier, and you don’t need any machine-learning expertise to get started.

Clinical Named Entity and Relationship Extraction (NERe)

Our Clinical NERe API allows developers to extract a wide range of essential medical information, encompassing medications, medical conditions, and diagnoses. Select Data’s solution goes beyond mere extraction by establishing fundamental connections to standard medical ontologies such as ICD-10-CM. For example, the term “heart failure” can be linked to the viable code “I50.9,” facilitating standardized and accurate classification. It also captures essential contextual information in the form of entity traits. These traits, such as negation, provide crucial insights into the semantics and nuances associated with the extracted medical information.


Customizing your cNLP pipeline empowers your organization to unlock the full potential of NLP technology and harness it as a strategic advantage in driving innovation. These benefits collectively enhance the utility and effectiveness of the pipeline, enabling organizations to tap into valuable insights from clinical text and drive improvements in patient care, research, and operational efficiency.

No machine learning experience required

Enjoy the benefits of a fully managed solution with SmartCare APIs. Eliminate the need for server provisioning and the complexities of building, training, and deploying machine learning models. SmartCare empowers developers to focus on what matters most—creating innovative healthcare applications without the hassle.


Relevance to Specific Use Cases

Different healthcare domains and applications have unique needs, such as specific clinical specialties or post-acute setting features. Customization allows the pipeline to focus on relevant information and deliver more accurate results, improving its effectiveness and usability for specific use cases.

Enhanced Accuracy

Every healthcare organization faces challenges and intricacies when dealing with medical text. Customizing the cNLP pipeline enables fine-tuning the algorithms, models, and configurations to adapt to these specific challenges. This customization can lead to improved accuracy in extracting and understanding clinical information.

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Integration with Existing Systems

By customizing the cNLP pipeline, it can seamlessly integrate with EHRs or clinical decision support systems, ensuring alignment with the organization’s infrastructure and processes. This integration promotes efficient data utilization and interoperability, enabling smooth operations within the organization.

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