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Comprehensively identifying Long Covid articles with human-in-the-loop machine learning.
Leaman, Robert; Islamaj, Rezarta; Allot, Alexis; Chen, Qingyu; Wilbur, W John; Lu, Zhiyong.
  • Leaman R; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 8600 Rockville Pike, Bethesda, MD, 20894, USA.
  • Islamaj R; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 8600 Rockville Pike, Bethesda, MD, 20894, USA.
  • Allot A; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 8600 Rockville Pike, Bethesda, MD, 20894, USA.
  • Chen Q; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 8600 Rockville Pike, Bethesda, MD, 20894, USA.
  • Wilbur WJ; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 8600 Rockville Pike, Bethesda, MD, 20894, USA.
  • Lu Z; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 8600 Rockville Pike, Bethesda, MD, 20894, USA.
Patterns (N Y) ; : 100659, 2022 Dec 01.
Article in English | MEDLINE | ID: covidwho-2242541
ABSTRACT
A significant percentage of COVID-19 survivors experience ongoing multisystemic symptoms that often affect daily living, a condition known as Long Covid or post-acute-sequelae of SARS-CoV-2 infection. However, identifying scientific articles relevant to Long Covid is challenging since there is no standardized or consensus terminology. We developed an iterative human-in-the-loop machine learning framework combining data programming with active learning into a robust ensemble model, demonstrating higher specificity and considerably higher sensitivity than other methods. Analysis of the Long Covid collection shows that (1) most Long Covid articles do not refer to Long Covid by any name (2) when the condition is named, the name used most frequently in the literature is Long Covid, and (3) Long Covid is associated with disorders in a wide variety of body systems. The Long Covid collection is updated weekly and is searchable online at the LitCovid portal https//www.ncbi.nlm.nih.gov/research/coronavirus/docsum?filters=e_condition.LongCovid.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid Language: English Journal: Patterns (N Y) Year: 2022 Document Type: Article Affiliation country: J.patter.2022.100659

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid Language: English Journal: Patterns (N Y) Year: 2022 Document Type: Article Affiliation country: J.patter.2022.100659