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Pregled bibliografske jedinice broj: 1158817

COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review


Suri, Jasjit S; Puvvula, Anudeep; Biswas, Mainak; Majhail, Misha; Saba, Luca; Faa, Gavino; Singh, Inder M.; Oberleitner, Ronald; Turk, Monika; Chadha, Paramjit S et al.
COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review // Computers in biology and medicine, 124 (2020), 103960, 15 doi:10.1016/j.compbiomed.2020.103960 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1158817 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review

Autori
Suri, Jasjit S ; Puvvula, Anudeep ; Biswas, Mainak ; Majhail, Misha ; Saba, Luca ; Faa, Gavino ; Singh, Inder M. ; Oberleitner, Ronald ; Turk, Monika ; Chadha, Paramjit S ; Johri, Amer M ; Sanches, J Miguel ; Khanna, Narendra N ; Viskovic, Klaudija ; Mavrogeni, Sophie ; Laird, John R ; Pareek, Gyan ; Miner, Martin ; Sobel, David W. ; Balestrieri, Antonella ; Sfikakis, Petros P ; Tsoulfas, George ; Protogerou, Athanasios ; Misra, Durga Prasanna ; Agarwal, Vikas ; Kitas, George D. ; Ahluwalia, Puneet ; Kolluri, Raghu ; Teji, Jagjit ; Maini, Mustafa Al ; Agbakoba, Ann ; Dhanjil, Surinder K. ; Sockalingam, Meyypan ; Saxena, Ajit ; Nicolaides, Andrew ; Sharma, Aditya ; Rathore, Vijay ; Ajuluchukwu, Janet N.A. ; Fatemi, Mostafa ; Alizad, Azra ; Viswanathan, Vijay ; Krishnan, Pudukode R ; Naidu, Subbaram

Izvornik
Computers in biology and medicine (0010-4825) 124 (2020); 103960, 15

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
COVID-19 ; comorbidity ; pathophysiology ; heart ; brain ; lung ; imaging ; artificial intelligence ; risk assessment

Sažetak
Artificial intelligence (AI) has penetrated the field of medicine, particularly the field of radiology. Since its emergence, the highly virulent coronavirus disease 2019 (COVID-19) has infected over 10 million people, leading to over 500, 000 deaths as of July 1st, 2020. Since the outbreak began, almost 28, 000 articles about COVID-19 have been published (https://pubmed.ncbi.nlm.nih.gov) ; however, few have explored the role of imaging and artificial intelligence in COVID-19 patients—specifically, those with comorbidities. This paper begins by presenting the four pathways that can lead to heart and brain injuries following a COVID-19 infection. Our survey also offers insights into the role that imaging can play in the treatment of comorbid patients, based on probabilities derived from COVID-19 symptom statistics. Such symptoms include myocardial injury, hypoxia, plaque rupture, arrhythmias, venous thromboembolism, coronary thrombosis, encephalitis, ischemia, inflammation, and lung injury. At its core, this study considers the role of image-based AI, which can be used to characterize the tissues of a COVID-19 patient and classify the severity of their infection. Image- based AI is more important than ever as the pandemic surges and countries worldwide grapple with limited medical resources for detection and diagnosis.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti



POVEZANOST RADA


Ustanove:
Klinika za infektivne bolesti "Dr Fran Mihaljević"

Profili:

Avatar Url Klaudija Višković (autor)

Poveznice na cjeloviti tekst rada:

doi www.ncbi.nlm.nih.gov www.sciencedirect.com

Citiraj ovu publikaciju:

Suri, Jasjit S; Puvvula, Anudeep; Biswas, Mainak; Majhail, Misha; Saba, Luca; Faa, Gavino; Singh, Inder M.; Oberleitner, Ronald; Turk, Monika; Chadha, Paramjit S et al.
COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review // Computers in biology and medicine, 124 (2020), 103960, 15 doi:10.1016/j.compbiomed.2020.103960 (međunarodna recenzija, članak, znanstveni)
Suri, J., Puvvula, A., Biswas, M., Majhail, M., Saba, L., Faa, G., Singh, I., Oberleitner, R., Turk, M. & Chadha, P. (2020) COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review. Computers in biology and medicine, 124, 103960, 15 doi:10.1016/j.compbiomed.2020.103960.
@article{article, author = {Suri, Jasjit S and Puvvula, Anudeep and Biswas, Mainak and Majhail, Misha and Saba, Luca and Faa, Gavino and Singh, Inder M. and Oberleitner, Ronald and Turk, Monika and Chadha, Paramjit S and Johri, Amer M and Sanches, J Miguel and Khanna, Narendra N and Viskovic, Klaudija and Mavrogeni, Sophie and Laird, John R and Pareek, Gyan and Miner, Martin and Sobel, David W. and Balestrieri, Antonella and Sfikakis, Petros P and Tsoulfas, George and Protogerou, Athanasios and Misra, Durga Prasanna and Agarwal, Vikas and Kitas, George D. and Ahluwalia, Puneet and Kolluri, Raghu and Teji, Jagjit and Maini, Mustafa Al and Agbakoba, Ann and Dhanjil, Surinder K. and Sockalingam, Meyypan and Saxena, Ajit and Nicolaides, Andrew and Sharma, Aditya and Rathore, Vijay and Ajuluchukwu, Janet N.A. and Fatemi, Mostafa and Alizad, Azra and Viswanathan, Vijay and Krishnan, Pudukode R and Naidu, Subbaram}, year = {2020}, pages = {15}, DOI = {10.1016/j.compbiomed.2020.103960}, chapter = {103960}, keywords = {COVID-19, comorbidity, pathophysiology, heart, brain, lung, imaging, artificial intelligence, risk assessment}, journal = {Computers in biology and medicine}, doi = {10.1016/j.compbiomed.2020.103960}, volume = {124}, issn = {0010-4825}, title = {COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review}, keyword = {COVID-19, comorbidity, pathophysiology, heart, brain, lung, imaging, artificial intelligence, risk assessment}, chapternumber = {103960} }
@article{article, author = {Suri, Jasjit S and Puvvula, Anudeep and Biswas, Mainak and Majhail, Misha and Saba, Luca and Faa, Gavino and Singh, Inder M. and Oberleitner, Ronald and Turk, Monika and Chadha, Paramjit S and Johri, Amer M and Sanches, J Miguel and Khanna, Narendra N and Viskovic, Klaudija and Mavrogeni, Sophie and Laird, John R and Pareek, Gyan and Miner, Martin and Sobel, David W. and Balestrieri, Antonella and Sfikakis, Petros P and Tsoulfas, George and Protogerou, Athanasios and Misra, Durga Prasanna and Agarwal, Vikas and Kitas, George D. and Ahluwalia, Puneet and Kolluri, Raghu and Teji, Jagjit and Maini, Mustafa Al and Agbakoba, Ann and Dhanjil, Surinder K. and Sockalingam, Meyypan and Saxena, Ajit and Nicolaides, Andrew and Sharma, Aditya and Rathore, Vijay and Ajuluchukwu, Janet N.A. and Fatemi, Mostafa and Alizad, Azra and Viswanathan, Vijay and Krishnan, Pudukode R and Naidu, Subbaram}, year = {2020}, pages = {15}, DOI = {10.1016/j.compbiomed.2020.103960}, chapter = {103960}, keywords = {COVID-19, comorbidity, pathophysiology, heart, brain, lung, imaging, artificial intelligence, risk assessment}, journal = {Computers in biology and medicine}, doi = {10.1016/j.compbiomed.2020.103960}, volume = {124}, issn = {0010-4825}, title = {COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review}, keyword = {COVID-19, comorbidity, pathophysiology, heart, brain, lung, imaging, artificial intelligence, risk assessment}, chapternumber = {103960} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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