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BEGIN:VEVENT
DTSTAMP:20250313T150347Z
DTSTART:20250402T150000Z
DTEND:20250402T160000Z
SUMMARY:CarDIA-AI: Improving outcomes and lowering costs of cardiac imagi
 ng by optimizing patient selection using Artificial Intelligence with Dr
  Jon Parkinson\, Dr Lamiece Hassan and guest Dr Jeremy Petch
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}t1v5-m87hbl
 x0-kedoyd
DESCRIPTION:\nDr Jon Parkinson is very happy to announce that he and Dr L
 amiece Hassan are hosting their next AI in Healthcare seminar on April 2
 nd at 16:00 in the Congregation room in Vaughan House when Dr Jeremy Pet
 ch\, an Associate Professor at the University of Toronto will be deliver
 ing his talk: CarDIA-AI: Improving outcomes and lowering costs of cardia
 c imaging by optimizing patient selection using Artificial Intelligence\
 n\nCoronary 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 r
 eceive ICA are found to have either no disease or non-significant CAD\, 
 meaning that while they receive a definitive diagnosis\, they do not rec
 eive any therapeutic benefit. This is of concern because ICA is an expen
 sive procedure\, and it carries a small but real risk to patients (rough
 ly 1/1000 ICAs results in stroke\, heart attack and/or death). More rece
 ntly\, a non-invasive diagnostic test\, cardiac computed tomographic ang
 iography (CCTA)\, has been shown to be as effective as ICA at diagnosing
  CAD in the right patient population\, while being significantly less ex
 pensive and less risky for patients. However\, testing every patient wit
 h CCTA results in high rates of double-testing\, which is costly and exp
 oses patients to additional radiation.\n\nWe 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 dir
 ectly to ICA\, to receive both a diagnosis and therapeutic benefit from 
 revascularization. We have integrated this screening tool into a central
 ized triage model to ensure that every patient gets the test that is bes
 t for them. We are now evaluating the AI tool combined with the centrali
 zed triage pathway through a multisite randomized control trial at Hamil
 ton 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.\n\nBio: Dr. Jeremy Petch is the founder and 
 Director of CREATE (CentRE for dAta science and digiTal hEalth)\, a mult
 idisciplinary research and innovation team with expertise in digital hea
 lth and clinical artificial intelligence\, located at Hamilton Health Sc
 iences. He is an Associate Professor at the Institute for Health Policy\
 , Management and Evaluation at the University of Toronto and an Associat
 e Investigator at the Population Health Research Institute. Prior to joi
 ning HHS\, he led St. Michael’s Hospital’s transformation into a data-dr
 iven organization\, through the deployment of an advanced data and analy
 tics infrastructure and co-founding the Li Ka Shing Centre for Healthcar
 e Analytics Research and Training (LKS-CHART). Dr. Petch is contributing
  to the development of international standards for responsible AI develo
 pment in healthcare through ISO’s committee 215 on Health Informatics. H
 e was previously a core member of CADTH’s Health Technology Expert Revie
 w Panel\, chair of the board of Regent Park Community Health Centre\, an
 d co-chair of the Greater Hamilton Health Network’s Digital Health Secre
 tariat.\nThe talk will be open for both in-person and online attendance.
 \n\n\nJon Parkinson\, PhD | Lecturer in Clinical Data Science | Division
  of Informatics\, Imaging & Data Sciences | The University of Manchester
 \nRoom G.526 | Stopford Building |Oxford Road | Manchester M13 9PT\nPhon
 e: Mobile: +44(0)7866 413299 Landline: +44(161) 306 9399\n\n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Congregation Room\, Vaughan House\, Manchester
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