| Autor: |
Suri, Jasjit S. Puvvula, Anudeep Majhail, Misha Biswas, Mainak Jamthikar, Ankush D. Saba, Luca Faa, Gavino and Singh, Inder M. Oberleitner, Ronald Turk, Monika Srivastava, Saurabh Chadha, Paramjit S. Suri, Harman S. Johri, Amer M. and Nambi, Vijay Sanches, J. Miguel Khanna, Narendra N. and Viskovic, Klaudija Mavrogeni, Sophie Laird, John R. Bit, Arindam Pareek, Gyan Miner, Martin Balestrien, Antonella and Sfikakis, Petros P. Tsoulfas, George Protogerou, Athanasios and Misra, Durga Prasanna Agarwal, Vikas Kitas, George D. and Kolluri, Raghu Teji, Jagjit Porcu, Michele Al-Maini, Mustafa and Agbakoba, Ann Sockalingam, Meyypan Sexena, Ajit and Nicolaides, Andrew Sharma, Aditya Rathore, Vijay and Viswanathan, Vijay Naidu, Subbaram Bhatt, Deepak L. |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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