ARTICLE SUMMARY:
Artificial intelligence and machine learning could help solve one of the most vexing problems in respiratory disease: objectively quantifying and analyzing a person’s cough. Start-up Hyfe is at the forefront of this opportunity.
Artificial intelligence is a rapidly advancing analytics tool that is being applied to a growing variety of both clinical and consumer-generated healthcare data. Researchers are even using AI to analyze sound—such as voice or cough patterns—to help detect and characterize disease, an application aided by the fact that most people now carry around a microphone with them (in their smartphone) wherever they go.
Start-up Hyfe is targeting this space with several AI models designed to remotely track and interpret cough sounds. The company’s initial flagship product is an AI model it calls Alison, which seamlessly detects cough sounds and tracks their frequency. According to Hyfe’s co-founder and CEO, Joe Brew, assessing a patient’s cough is important when diagnosing and treating respiratory conditions; however, objective metrics on cough are often difficult to obtain.
