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10.31083/j.rcm.2020.04.236 http://scihub22266oqcxt.onion/10.31083/j.rcm.2020.04.236 33387999!ä!33387999 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Rev+Cardiovasc+Med 2020 ; 21 (4): 541-560 Nephropedia Template TP {{tp|p=33387999|t=2020. Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence |pdf=|usr=}}{{33387999}} gab.com Text Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence JO: Rev Cardiovasc Med http://www.kidney.de/pget.php?&tw=1&pmid=33387999 #FOAvip 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. Twit Text FOAVip Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence ????Rev Cardiovasc Med http://www.kidney.de/pget.php?&tw=1&pmid=33387999 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33387999 #FOAvip English Wikipedia <ref>{{Cite pmid|33387999}}</ref> Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence #MMPMID33387999 Suri JS; Puvvula A; Majhail M; Biswas M; Jamthikar AD; Saba L; Faa G; Singh IM; Oberleitner R; Turk M; Srivastava S; Chadha PS; Suri HS; Johri AM; Nambi V; Sanches JM; Khanna NN; Viskovic K; Mavrogeni S; Laird JR; Bit A; Pareek G; Miner M; Balestrieri A; Sfikakis PP; Tsoulfas G; Protogerou A; Misra DP; Agarwal V; Kitas GD; Kolluri R; Teji J; Porcu M; Al-Maini M; Agbakoba A; Sockalingam M; Sexena A; Nicolaides A; Sharma A; Rathore V; Viswanathan V; Naidu S; Bhatt DL Rev Cardiovasc Med 2020[Dec]; 21 (4): 541-560 PMID33387999show ga 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. |*Artificial Intelligence[MESH] |*Pandemics[MESH] |*Risk Assessment[MESH] |*SARS-CoV-2[MESH] |COVID-19/*epidemiology[MESH] |Cardiovascular Diseases/*epidemiology/therapy[MESH] |Comorbidity[MESH] |Delivery of Health Care/*methods[MESH] |Humans[MESH]Integration of cardiovascular risk assessment with COVID-19 using arti(epmc).pdf DeepDyve Pubget Overpricing