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Reviews in Cardiovascular Medicine  2020, Vol. 21 Issue (4): 541-560     DOI: 10.31083/j.rcm.2020.04.236
Special Issue: Utilizing Technology in the COVID 19 era
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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
1Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, 95747, CA, USA
2Annu's Hospitals for Skin and Diabetes, Nellore, 524001, AP, India
3Oakmount High School and AtheroPoint™, Roseville, 95747, CA, USA
4JIS University, Kolkata, 700001, West Bengal, India
5Department of ECE, Visvesvaraya National Institute of Technology, Nagpur, 440010, MH, India
6Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), 09100, Cagliari, Italy
7Department of Pathology, AOU of Cagliari, 09100, Italy
8Behavior Imaging, Boise, 83701, ID, USA
9The Hanse-Wissenschaftskolleg Institute for Advanced Study, 27749, Delmenhorst, Germany
10School of Computing Science & Engineering, Galgotias University, 201301, Gr. Noida, India
11Brown University, Providence, 02912, RI, USA
12Department of Medicine, Division of Cardiology, Queen's University, Kingston, B0P 1R0, Ontario, Canada
13Department of Cardiology, Baylor College of Medicine, 77001, TX, USA
14Institute of Systems and Robotics, Instituto Superior Tecnico, 1000-001, Lisboa, Portugal
15Department of Cardiology, Indraprastha APOLLO Hospitals, 110001, New Delhi, India
16University Hospital for Infectious Diseases, 10000, Zagreb, Crotia
17Cardiology Clinic, Onassis Cardiac Surgery Center, 104 31, Athens, Greece
18Heart and Vascular Institute, Adventist Health St. Helena, St Helena, 94574, CA, USA
19Department of Biomedical Engineering, NIT, Raipur, 783334, CG, India
20Minimally Invasive Urology Institute, Brown University, Providence, 02901, Rhode Island, USA
21Men's Health Center, Miriam Hospital Providence, 02901, Rhode Island, USA
22Rheumatology Unit, National Kapodistrian University of Athens, 104 31, Greece
23Aristoteleion University of Thessaloniki, 544 53, Thessaloniki, Greece
24National & Kapodistrian University of Athens, 104 31, Greece
25Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, 226001, UP, India
26Academic Affairs, Dudley Group NHS Foundation Trust, DY1, Dudley, UK
27Arthritis Research UK Epidemiology Unit, Manchester University, M13, Manchester, UK
28OhioHealth Heart and Vascular, 45874, Ohio, USA
29Ann and Robert H. Lurie Children's Hospital of Chicago, 60601, Chicago, USA
30Allergy, Clinical Immunology and Rheumatology Institute, M3H 6A7, Toronto, Canada
31University of Lagos, 100001, Lagos, Nigeria
32MV Center of Diabetes, 600001, Chennai, India
33Vascular Screening and Diagnostic Centre and University of Nicosia Medical School, 999058, Cyprus
34Division of Cardiovascular Medicine, University of Virginia, Charlottesville, 22901, VA, USA
35Nephrology Department, Kaiser Permanente, Sacramento, 94203, CA, USA
36MV Hospital for Diabetes and Professor M Viswanathan Diabetes Research Centre, 600001, Chennai, India
37Electrical Engineering Department, University of Minnesota, Duluth, 55801, MN, USA
38Brigham and Women's Hospital Heart & Vascular Center, Harvard Medical School, Boston, 02108, MA, USA
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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 AIbased platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors.
Key words:  COVID-19      cardiovascular      myocarditis      artificial intelligence      risk assessment      non-invasive monitoring     
Submitted:  02 November 2020      Revised:  03 December 2020      Accepted:  08 December 2020      Published:  30 December 2020     
*Corresponding Author(s):  Jasjit S. Suri     E-mail:

Cite this article: 

Jasjit S. Suri, Anudeep Puvvula, Misha Majhail, Mainak Biswas, Ankush D. Jamthikar, Luca Saba, Gavino Faa, Inder M. Singh, Ronald Oberleitner, Monika Turk, Saurabh Srivastava, Paramjit S. Chadha, Harman S. Suri, Amer M. Johri, Vijay Nambi, J Miguel Sanches , Narendra N. Khanna, Klaudija Viskovic, Sophie Mavrogeni, John R. Laird, Arindam Bit, Gyan Pareek, Martin Miner, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanasios Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Raghu Kolluri, Jagjit Teji, Michele Porcu, Mustafa Al-Maini, Ann Agbakoba, Meyypan Sockalingam, Ajit Sexena, Andrew Nicolaides, Aditya Sharma, Vijay Rathore, Vijay Viswanathan, Subbaram Naidu, Deepak L. Bhatt. Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence. Reviews in Cardiovascular Medicine, 2020, 21(4): 541-560.

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