A research initiative between RMIT University and digital health company DDM Health will look to the potential of artificial intelligence (AI) voice analysis technology to assess the risk of type 2 diabetes. If successful, the project could lead to improved health outcomes and reduced healthcare costs.

Type 2 diabetes is a global epidemic. Diagnosis can take several years after the onset of initial symptoms, by which time many patients have already developed serious health issues.

The collaborative project facilitated by the Digital Health Cooperative Research Centre (DHCRC) aims to significantly reduce this timelag between the onset of diabetes and diagnosis by developing an artificial intelligence model capable of analysing voice data to assess the risk of type 2 diabetes.

EMERGING EVIDENCE OF VOCAL BIOMARKERS

This approach is rooted in emerging evidence suggesting that vocal biomarkers can provide insights into various health conditions, including type 2 diabetes, mental health, heart failure, and certain neurological disorders.

“Type 2 diabetes is a global epidemic, affecting around 537 million people worldwide, and global spending on diabetes is US$966 billion annually, which equates to 11.5% of total health expenditure,” said Professor Barbora de Courten, project lead at RMIT University.

“This project offers a new frontier in noninvasive disease risk assessment and will pioneer the use of advanced machine learning algorithms to identify diabetes risk through voice patterns, pushing the boundaries of healthcare technology.

“This project will showcase the power of AI to transform healthcare by enabling early detection of diabetes through non-invasive voice analysis,” said Arjun Panesar, founding CEO of DDM Health.

“We’re developing a cutting-edge tool to predict diabetes risk by leveraging advanced AI and machine learning that will integrate seamlessly into global health applications.”

Current diagnostic methods for diabetes require a medical consultation and at least one blood test, if not a series of blood tests. It is hoped this vocal biomarker approach can pave the way for the development of an innovative, cost-effective, and non-invasive tool to alert people who potentially have type 2 diabetes to seek medical advice in a timely manner.

“The development and commercialisation of a voice-based diabetes risk prediction tool has the potential to provide a novel type 2 diabetes detection system for wide adoption within Australia, including remote, underserved communities,” said DHCRC CEO Annette Schmiede.

“As well as improved patient outcomes, this project has the potential to significantly reduce healthcare costs associated with type 2 diabetes and more broadly further strengthen and showcase the capability of the digital health industry in Australia.”