ResApp has raised $9.74 million for its new smartphone-based system designed to diagnose respiratory ailments.
ResApp’s offering essentially uses the smartphone microphone as a stethoscope to listen to a patient’s breathing. But instead of relying solely on a doctor’s ears to form a diagnosis from those sounds, ResApp has been developing machine-learning algorithms that will automatically determine which respiratory condition a patient might have, including pneumonia, asthma, bronchiolitis and COPD. In the future, the company hopes to integrate those algorithms into telehealth offerings as well as making them available for clinical use.
The company plans to use the new funds for its FDA clearance application and expand its offering in the US to in-clinic use, which includes emergency department and outpatient settings.
Earlier this month, ResApp released data from a recent clinical study of 524 pediatric patients that found their offering achieved an accuracy of 89 percent. The study was conducted by the company at Joondalup Health Campus (JHC) and Princess Margaret Hospital (PMH) in Perth, Western Australia.
Eighty-nine percent was the overall accuracy in differentiating between lower respiratory tract disease, upper respiratory tract infections, and healthy patients. In particular cases, the accuracy was much higher: for the differential diagnosis of croup, viral pneumonia, bronchiolitis and upper respiratory tract infections ResApp’s algorithms achieved accuracy levels between 90 and 98 percent. In a subset of patients that had been initially cleared by a doctor but diagnosed with lower respiratory tract disease after additional clinical testing, the ResApp diagnosed them correctly 97 percent of the time.
