LynxCare Blog

A metanalysis published in the Heart journal identified 37 studies developing and applying NLP in various areas of cardiology. This systematic review found that the majority of NLP work in cardiology has been concentrated in a small number of clinical domains and NLP methods, with the most common applications being used for disease identification and classification purposes. Patient sample sizes ranged from 60 to 621,000. Data sources ranged from single centers to national healthcare system databases and registries, most of them taking place in the US.

Since June 2022, LynxCare and PSIH Group have a strategic partnership, helping French hospitals to make the most of all their clinical data by building OMOP data warehouses (i.e. ‘EDS’) to improve patient care and research.

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's contributes to implementing these data warehouses.

Explore the transformative impact of LynxCare's AI and NLP technology on ATTR-CM detection, leading to a relative increase in genetic testing for this disease compared to manual checking of medical records.

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.

CB Insights has released its “Digital Health 150” 2022 list, ranking LynxCare among the 150 most promising digital health startups in the world.