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Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence

2020; IMR Press; Volume: 21; Issue: 4 Linguagem: Inglês

10.31083/j.rcm.2020.04.236

2153-8174

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, João Sanches, Narendra N. Khanna, Klaudija Višković, Sophie Mavrogeni, John R. Laird, Arindam Bit, Gyan Pareek, Martin Miner, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanase D. Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Raghu Kolluri, Jagjit S. 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,

Machine Learning in Healthcare

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.