AI-powered chest pain triage
aiTriage™ is a cleared medical device that turns a five-minute ECG into a risk score for major adverse cardiac events, so emergency departments and clinics can prioritise the patients at risk and identify those who may be suitable for earlier discharge. Developed in Singapore with leading hospitals and validated in peer-reviewed research.
Developed and studied with
The platform
aiTriage pairs a handheld 12-lead ECG with a tablet application and patented machine learning models. The result is a MACE risk score from 0 to 100 with a low, medium or high category, returned within minutes and validated with or without a troponin test.
Why chest pain
Chest pain is among the most common reasons to visit an emergency department, and the large majority of presentations are not acute coronary syndrome. Ruling out the few that are means serial troponin tests, observation and bed time for everyone. We built aiTriage to give clinicians an objective risk estimate at the point of triage.
Why we focus on chest pain triageClinician perspectives
aiTriage™ will help increase confidence to safely discharge patients at an earlier time and reduce crowding in the Emergency Department.
Dr. Ting Boon PingSengkang General Hospital, SingaporeaiTriage™ would help Emergency Departments ease the burden of doctors and nurses.
Dr. Chok LimsuwatBumrungrad International Hospital, BangkokNews
"Pilot Evaluation of a Novel Artificial Intelligence (AI) Heart Rate Variability (HRV)-Guided Risk Stratification for Chest Pain in the Emergency Department: A Randomized Controlled Trial" appears in Clinical and Experimental Emergency Medicine, the first randomised evaluation of the aiTriage approach in an emergency department.
Read more"Performance of a novel multimodal machine learning risk stratification tool (aiTriage v2.0) for chest pain patients presenting to the emergency department" appears as an abstract in a supplement to the Journal of the American College of Cardiology (volume 87, issue 13). It reports on the next-generation aiTriage models in emergency department chest pain patients.
Read moreAI models are increasingly relied upon by healthcare professionals to make decisions and treat patients. What does this mean for information disclosure practices? NUS Medicine’s Michael Dunn and Duke-NUS Medical School’s Liu Nan weigh in.
Read moreWalk through a live assessment with our team, or start with the peer-reviewed evidence behind the platform.