Prof Geoffrey A. Strange, PhD; Prof Michael P. Feneley, MD; Prof David Prior, MBBS PhD; Prof David Muller, MD; Dr Prasanna Venkataraman, MD; Dr Yiling Situ, MBBS; Prof Simon Stewart, DMSc; Prof David Playford, MBBS PhD
Professor Geoff Strange
The University of Notre Dame Australia
32 Mouat St, Fremantle WA 6160
E: [email protected]
T: +61 422 308 585
When compared to routine clinical detection and management, can machine learning/artificial intelligence (AI) techniques augment the detection of guideline-defined severe AS with potential to redirect more women and men to appropriate management?
An AI automated alert system (AI-AAS) specifically designed to detect severe AS
from routinely reported echocardiographic measurements, has the potential to
redirect 1.6 to 2.1-fold more men and women with guideline-defined severe AS
towards more definitive care from the heart care team.
A significant proportion of individuals (particularly women) being managed within a high-quality tertiary referral setting are potentially being overlooked for management of guideline defined, severe AS. If routinely applied, an AI-AAS has strong potential to appropriately redirect these individuals towards (consideration of) this life-saving treatment.
Echo IQ Limited
EchoSolv™ is currently available in the US and Australia as a guideline-led decision-support tool. Full
phenotyping capabilities will be available pending FDA approval.