Early diagnosis of pulmonary hypertension has become critical now that effective treatment options exist. A study has shown that Corvista Health’s machine-learned algorithm can accurately diagnose pulmonary hypertension in a non-invasive way by assessing the elevation of mean pulmonary arterial pressure (mPAP). This system could potentially transform the approach to pulmonary hypertension diagnosis as a frontline diagnostic tool.
The system is based on a procedure that can be performed during medical appointments in less than five minutes, with patients receiving results during the same visit. It uses algorithms to detect signs of specific conditions.
The results were published in the study “Clinical validation of a machine-learned, point-of-care system to identify pulmonary hypertension” in European Respiratory Journal Open Research.
Read more at this link on the Pulmonary Hypertension News