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CarDIA-AI: Improving outcomes and lowering costs of cardiac imaging by optimizing patient selection using Artificial Intelligence with Dr Jon Parkinson, Dr Lamiece Hassan and guest Dr Jeremy Petch

Dates:2 April 2025
Times:16:00 - 17:00
What is it:Seminar
Organiser:Faculty of Biology, Medicine and Health
Who is it for:University staff
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  • https://www.eventbrite.co.uk/e/cardia-ai-improving-outcomes-and-costs-of-cardiac-imaging-tickets-1283992910359

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  • By Faculty of Biology, Medicine and Health

Dr Jon Parkinson is very happy to announce that he and Dr Lamiece Hassan are hosting their next AI in Healthcare seminar on April 2nd at 16:00 in the Congregation room in Vaughan House when Dr Jeremy Petch, an Associate Professor at the University of Toronto will be delivering his talk: CarDIA-AI: Improving outcomes and lowering costs of cardiac imaging by optimizing patient selection using Artificial Intelligence

Coronary artery disease (CAD) is the leading cause of death worldwide. For decades, the gold-standard test used to diagnose CAD was invasive coronary angiography (ICA). However, nearly half of the patients who receive ICA are found to have either no disease or non-significant CAD, meaning that while they receive a definitive diagnosis, they do not receive any therapeutic benefit. This is of concern because ICA is an expensive procedure, and it carries a small but real risk to patients (roughly 1/1000 ICAs results in stroke, heart attack and/or death). More recently, a non-invasive diagnostic test, cardiac computed tomographic angiography (CCTA), has been shown to be as effective as ICA at diagnosing CAD in the right patient population, while being significantly less expensive and less risky for patients. However, testing every patient with CCTA results in high rates of double-testing, which is costly and exposes patients to additional radiation.

We have developed an AI model to accurately identify which patients are good candidates for CCTA (i.e., likely to have either no or mild CAD) versus which should proceed directly to ICA, to receive both a diagnosis and therapeutic benefit from revascularization. We have integrated this screening tool into a centralized triage model to ensure that every patient gets the test that is best for them. We are now evaluating the AI tool combined with the centralized triage pathway through a multisite randomized control trial at Hamilton Health Sciences and Niagara Health. The coal of this intervention is to reduce risk to patients, reduce wait times for ICA and reduce costs to the health care system.

Bio: Dr. Jeremy Petch is the founder and Director of CREATE (CentRE for dAta science and digiTal hEalth), a multidisciplinary research and innovation team with expertise in digital health and clinical artificial intelligence, located at Hamilton Health Sciences. He is an Associate Professor at the Institute for Health Policy, Management and Evaluation at the University of Toronto and an Associate Investigator at the Population Health Research Institute. Prior to joining HHS, he led St. Michael’s Hospital’s transformation into a data-driven organization, through the deployment of an advanced data and analytics infrastructure and co-founding the Li Ka Shing Centre for Healthcare Analytics Research and Training (LKS-CHART). Dr. Petch is contributing to the development of international standards for responsible AI development in healthcare through ISO’s committee 215 on Health Informatics. He was previously a core member of CADTH’s Health Technology Expert Review Panel, chair of the board of Regent Park Community Health Centre, and co-chair of the Greater Hamilton Health Network’s Digital Health Secretariat. The talk will be open for both in-person and online attendance.

Jon Parkinson, PhD | Lecturer in Clinical Data Science | Division of Informatics, Imaging & Data Sciences | The University of Manchester Room G.526 | Stopford Building |Oxford Road | Manchester M13 9PT Phone: Mobile: +44(0)7866 413299 Landline: +44(161) 306 9399

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Congregation Room
Vaughan House
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Madeleine Ryan

07872986408

madeleine.ryan@manchester.ac.uk

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