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ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163531/ http://dx.doi.org/10.1016/j.neurom.2022.02.160 |
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author | Rauck, Richard Berger, Sara Cecchi, Guillermo Agurto, Carla Eyigoz, Elif Lechleiter, Kristen Huynh, Dat Brad Hershey Loudermilk, Eric Paez, Julio Bojrab, Louis Noles, John Turley, Todd Ibrahim, Mohab Patwardhan, Amol Scowcroft, James Rene Przkora Miller, Nathan Chaiban, Gassan Matt McDonald Rogers, Jeffrey |
author_facet | Rauck, Richard Berger, Sara Cecchi, Guillermo Agurto, Carla Eyigoz, Elif Lechleiter, Kristen Huynh, Dat Brad Hershey Loudermilk, Eric Paez, Julio Bojrab, Louis Noles, John Turley, Todd Ibrahim, Mohab Patwardhan, Amol Scowcroft, James Rene Przkora Miller, Nathan Chaiban, Gassan Matt McDonald Rogers, Jeffrey |
author_sort | Rauck, Richard |
collection | PubMed |
description | |
format | Online Article Text |
id | pubmed-9163531 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91635312022-06-04 ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience Rauck, Richard Berger, Sara Cecchi, Guillermo Agurto, Carla Eyigoz, Elif Lechleiter, Kristen Huynh, Dat Brad Hershey Loudermilk, Eric Paez, Julio Bojrab, Louis Noles, John Turley, Todd Ibrahim, Mohab Patwardhan, Amol Scowcroft, James Rene Przkora Miller, Nathan Chaiban, Gassan Matt McDonald Rogers, Jeffrey Neuromodulation Article Published by Elsevier Inc. 2022-06 2022-06-03 /pmc/articles/PMC9163531/ http://dx.doi.org/10.1016/j.neurom.2022.02.160 Text en Copyright © 2022 Published by Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Rauck, Richard Berger, Sara Cecchi, Guillermo Agurto, Carla Eyigoz, Elif Lechleiter, Kristen Huynh, Dat Brad Hershey Loudermilk, Eric Paez, Julio Bojrab, Louis Noles, John Turley, Todd Ibrahim, Mohab Patwardhan, Amol Scowcroft, James Rene Przkora Miller, Nathan Chaiban, Gassan Matt McDonald Rogers, Jeffrey ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience |
title | ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience |
title_full | ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience |
title_fullStr | ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience |
title_full_unstemmed | ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience |
title_short | ID:15982 Chronic Pain Patients During COVID-19: Machine Learning Reveals Attributes Leading to Pandemic Susceptibility and Resilience |
title_sort | id:15982 chronic pain patients during covid-19: machine learning reveals attributes leading to pandemic susceptibility and resilience |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163531/ http://dx.doi.org/10.1016/j.neurom.2022.02.160 |
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