Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic “cognitive” functions that we associate with our mind, such as “learning” and “solving problem”. New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors.
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Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence
Jasjit S. Suri1,*, Anudeep Puvvula1,2, Misha Majhail1,3, Mainak Biswas4, Ankush D. Jamthikar5, Luca Saba6, Gavino Faa7, Inder M. Singh1, Ronald Oberleitner8, Monika Turk9, Saurabh Srivastava10, Paramjit S. Chadha1, Harman S. Suri11, Amer M. Johri12, Vijay Nambi13, J Miguel Sanches14, Narendra N. Khanna15, Klaudija Viskovic16, Sophie Mavrogeni17, John R. Laird18, Arindam Bit19, Gyan Pareek20, Martin Miner21, Antonella Balestrieri6, Petros P. Sfikakis22, George Tsoulfas23, Athanasios Protogerou24, Durga Prasanna Misra25, Vikas Agarwal25, George D. Kitas26,27, Raghu Kolluri28, Jagjit Teji29, Michele Porcu6, Mustafa Al-Maini30, Ann Agbakoba31, Meyypan Sockalingam32, Ajit Sexena15, Andrew Nicolaides33, Aditya Sharma34, Vijay Rathore35, Vijay Viswanathan36, Subbaram Naidu37, Deepak L. Bhatt38
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1
Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, 95747, CA, USA
2
Annu’s Hospitals for Skin and Diabetes, Nellore, 524001, AP, India
3
Oakmount High School and AtheroPoint™, Roseville, 95747, CA, USA
4
JIS University, Kolkata, 700001, West Bengal, India
5
Department of ECE, Visvesvaraya National Institute of Technology, Nagpur, 440010, MH, India
6
Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), 09100, Cagliari, Italy
7
Department of Pathology, 09100, AOU of Cagliari, Italy
8
Behavior Imaging, Boise, 83701, ID, USA
9
The Hanse-Wissenschaftskolleg Institute for Advanced Study, 27749, Delmenhorst, Germany
10
School of Computing Science & Engineering, Galgotias University, 201301, Gr. Noida, India
11
Brown University, Providence, 02912, RI, USA
12
Department of Medicine, Division of Cardiology, Queen’s University, Kingston, B0P 1R0, Ontario, Canada
13
Department of Cardiology, Baylor College of Medicine, 77001, TX, USA
14
Institute of Systems and Robotics, Instituto Superior Tecnico, 1000-001, Lisboa, Portugal
15
Department of Cardiology, Indraprastha APOLLO Hospitals, 110001, New Delhi, India
16
University Hospital for Infectious Diseases, 10000, Zagreb, Crotia
17
Cardiology Clinic, Onassis Cardiac Surgery Center, 104 31, Athens, Greece
18
Heart and Vascular Institute, Adventist Health St. Helena, St Helena, 94574, CA, USA
19
Department of Biomedical Engineering, NIT, Raipur, 783334, CG, India
20
Minimally Invasive Urology Institute, Brown University, Providence, 02901, Rhode Island, USA
21
Men’s Health Center, Miriam Hospital Providence, 02901, Rhode Island, USA
22
Rheumatology Unit, National Kapodistrian University of Athens, 104 31, Greece
23
Aristoteleion University of Thessaloniki, 544 53, Thessaloniki, Greece
24
National & Kapodistrian University of Athens, 104 31, Greece
25
Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, 226001, UP, India
26
Academic Affairs, Dudley Group NHS Foundation Trust, DY1, Dudley, UK
27
Arthritis Research UK Epidemiology Unit, Manchester University, M13, Manchester, UK
28
OhioHealth Heart and Vascular, 45874, Ohio, USA
29
Ann and Robert H. Lurie Children’s Hospital of Chicago, 60601, Chicago, USA
30
Allergy, Clinical Immunology and Rheumatology Institute, M3H 6A7, Toronto, Canada
31
University of Lagos, 100001, Lagos, Nigeria
32
MV Center of Diabetes, 600001, Chennai, India
33
Vascular Screening and Diagnostic Centre and University of Nicosia Medical School, 999058, Cyprus
34
Division of Cardiovascular Medicine, University of Virginia, Charlottesville, 22901, VA, USA
35
Nephrology Department, Kaiser Permanente, Sacramento, 94203, CA, USA
36
MV Hospital for Diabetes and Professor M Viswanathan Diabetes Research Centre, 600001, Chennai, India
37
Electrical Engineering Department, University of Minnesota, Duluth, 55801, MN, USA
38
Brigham and Women’s Hospital Heart & Vascular Center, Harvard Medical School, Boston, 02108, MA, USA
*Correspondence: jasjit.suri@atheropoint.com (Jasjit S. Suri)
Rev. Cardiovasc. Med. 2020, 21(4), 541–560;
https://doi.org/10.31083/j.rcm.2020.04.236
Submitted: 2 November 2020 | Revised: 3 December 2020 | Accepted: 8 December 2020 | Published: 30 December 2020
(This article belongs to the Special Issue Utilizing Technology in the COVID 19 era)
Copyright: © 2020 Suri et al. Published by IMR Press.
This is an open access article under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/).
Abstract
Keywords
COVID-19
cardiovascular
myocarditis
artificial intelligence
risk assessment
non-invasive monitoring
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