Health AI Central
Share:
Peer-Reviewed Publication
Eur Heart J Digit Health2026;7(3):ztag037.April 1, 2026Journal Article

Fully automated, deep learning, cardiac CT-based multimodal network for cardiovascular risk stratification in high-risk perioperative patients.

Juan Lu1,2,3, Gavin Huangfu1,2,4, Abdul Ihdayhid4, Mohammed Bennamoun3, John Konstantopoulos5, Simon Kwok5, Kai Niu3,5, Yanbin Liu6, Gemma A Figtree7,8, Matthew T V Chan9, Craig R Butler10, Vikas Tandon11, Peter Nagele12, Pamela K Woodard13, Marko Mrkobrada14, Wojciech Szczeklik15, Yang Faridah Abdul Aziz16, Bruce M Biccard17, Philip James Devereaux11, Tej Sheth11, Michelle C Williams18, David E Newby18, Benjamin J W Chow19, Girish Dwivedi1,2,4,19,20
1Medical School, The University of Western Australia, Perth, Australia.
2Harry Perkins Institute of Medical Research, Perth, Australia.
3Department of Computer Science and Software Engineering, The University of Western Australia, Perth, Australia.
4Department of Cardiology, Fiona Stanley Hospital, Perth, Australia.
5Artrya Ltd, Perth, Australia.
6School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
7Department of Cardiology, Kolling Institute and Charles Perkins Centre, University of Sydney, Sydney, Australia.
8Department of Cardiology, Royal North Shore Hospital, Sydney, Australia.
9Department of Anesthesia and Intensive Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
10Division of Cardiology, University of Alberta Hospital, Edmonton, Alberta, Canada.
11Department of Medicine, McMaster University, Hamilton, Canada.
12Department of Anaesthesia & Critical Care, The University of Chicago, Chicago, USA.
13Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
14Department of Medicine, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
15Department of Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakόw, Poland.
16Departments of Radiology and Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
17Department of Anaesthesia and Perioperative Medicine, Groote Schuur Hospital, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
18Department of Medicine, University of Edinburgh, Edinburgh, UK.
19Department of Medicine (Cardiology), University of Ottawa Heart Institute, Ottawa, Canada.
20Department of Cardiology, Victor Chang Cardiac Research Institute, Crawley, WA 6009, Australia.
PubMed PMC DOI PDF

Abstract

AIMS: Major adverse cardiac events (MACE) significantly impact perioperative morbidity and mortality. We aimed to develop a fully automated multimodal deep learning (DL) system integrating patient demographics, comorbidities, and coronary computed tomography angiography (CCTA) findings to optimize risk prediction. METHODS AND RESULTS: We included 639 patients undergoing CCTA as part of perioperat…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.