Exploring the Promise of AI-NLP in Early Detection of Fatal Cardiomyopathy

How can integrating AI-NLP technology into clinical practice aid in the earlier detection of conditions like ATTR-CM. Dive into our joint publication with Heart Center Aalst, where we explored how AI-NLP technology was harnessed to identify high-risk patients with ATTR-CM.
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‍Published in ESC Heart Failure.

‍Unveiling Insights into Heart Failure leveraging cutting-edge AI technology

Through a retrospective study, in collaboration with Heart Center Aalst, we aimed to delve deep into the complexities of heart failure. Using advanced NLP algorithms, we were able to collect and analyze clinical data from a real-world cohort of 1000+ heart failure patients diagnosed with HFrEF or HFmrE.
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‍Published in ESC Heart Failure.

‍Data from EHRs reveals insights on a real-world heart failure population

A multi-country study indicates 1-2% of adults have heart failure, potentially rising to 4%. Analyzing national registries and EHRs offers deeper understanding of the burden of heart failure on patients and on our healthcare systems.
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‍Published in Heart.

‍Bridging Gaps in Heart Failure Research

Clinical trials often exclude patients with significant comorbidities, limiting real-world representation. LynxCare’s Heart Failure datasets offer invaluable insights into the interplay between specific comorbidities, adverse events, and treatment outcomes in heart failure patients, addressing this crucial knowledge gap and guiding comprehensive care decisions.
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At LynxCare, we are committed to advancing cardiovascular care through facilitating innovative research. Together, we can make meaningful strides towards improving outcomes for heart failure patients.