LynxCare Blog

Lung cancer claims millions of lives worldwide every year. And there’s no single cure. But what if we could gain deeper insights into the genetic makeup of a population of 30,000+ lung cancer patients? Thanks to our Natural Language Processing (NLP) algorithm and a team of dedicated researchers, we now have a clearer picture of the non-small cell lung cancer (NSCLC) patient population and the specific genetic mutations that drive tumor growth. In this blog, we’ll share our AI-driven findings from the Dutch nationwide registry of histo- and cyto-pathology (PALGA) registry. Read on to discover how AI data processing with 95.9% accuracy can propel the progress of cancer treatment. ‍

Muco is an association by and for people with cystic fibrosis and their families. Together with families, muco centers and healthcare providers, the association is committed to ensuring a better, longer and happier life for all muco patients.

Cancer research is the most rapidly advancing field of medical science – largely driven by the emergence of accessible and high-quality clinical data. LynxCare's NLP algorithm is benefiting gastrointestinal (GI) cancer research by offering new insights into this group of complicated diseases. In this article you’ll learn how this cutting-edge technology has enabled the mapping of unstructured data from over 24,500 health records, with precision and recall rates reaching 94%. We’ll highlight the unique capabilities of AI in unlocking the potential of real-world evidence (RWE), including examples from our use case for esophageal, pancreatic, and gastric cancers.

Rare diseases, such as hATTR polyneuropathy, are a major diagnostic challenge. The biggest obstacle? The lack of specific symptoms in hATTR polyneuropathy, which doesn’t allow for its early diagnosis, lowering the patient’s chances of getting timely access to the right treatment. Read on to learn how an AI-driven framework using Natural Language Processing (NLP) can detect hATTR red flag symptoms in Electronic Health Records (EHRs), leading to a 48.6% relative increase in genetic testing for this condition.

In May 2022, the European Commission announced the launch of the European Health Data Space (EHDS), one of the central building blocks of a strong European Health Union. The EHDS will help the EU to achieve a quantum leap forward in the way healthcare is provided to people across Europe.

In this blogpost, we discuss the significance of OHDSI, OMOP, and EHDEN in improving healthcare through data standardization and efficient analysis. We detail the advantages of OMOP CDM data warehouses for hospitals and showcase how LynxCare contributes to implementing these data warehouses.