학술논문
Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence
Document Type
article
Author
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
Source
Reviews in Cardiovascular Medicine, Vol 21, Iss 4, Pp 541-560 (2020)
Subject
Language
English
ISSN
1530-6550
Abstract
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.