About LynxCare

NLP | Video | Transforming healthcare information through accurate and efficient data processing

In today’s healthcare landscape, accurate and efficient data processing is critical. LynxCare’s proprietary disease-specific data mining models can revolutionize this process. To highlight the full potential of our Natural Language Processing (NLP) technology, we invite you to explore a demo that showcases how our technology performs across multiple languages in diverse healthcare contexts.

In this About LynxCare you’ll learn:

In this article you’ll learn:

LynxCare’s NLP pipeline is able to process complex EHR data in multiple languages, linking medical information to a knowledge base and integrating it into the hospital’s OMOP Common Data Model. This ensures accurate and efficient handling of complex medical data, even in multilingual environments, without manual data processing.

Contact us to receive a live demo.

Please note: Our NLP technology does not enable speech-to-text functionality.

LynxCare’s NLP pipeline is able to process complex EHR data in multiple languages, linking medical information to a knowledge base and integrating it into the hospital’s OMOP Common Data Model. This ensures accurate and efficient handling of complex medical data, even in multilingual environments, without manual data processing.

Contact us to receive a live demo.

Please note: Our NLP technology does not enable speech-to-text functionality.

About LynxCare

NLP | Video | Transforming healthcare information through accurate and efficient data processing

In today’s healthcare landscape, accurate and efficient data processing is critical. LynxCare’s proprietary disease-specific data mining models can revolutionize this process. To highlight the full potential of our Natural Language Processing (NLP) technology, we invite you to explore a demo that showcases how our technology performs across multiple languages in diverse healthcare contexts.

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WATCH FULL VIDEO
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Discover the capabilities of LynxCare’s NLP pipeline through a demo, showcasing how our system performs across multiple languages in diverse healthcare contexts.

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