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Giving a Voice to Patients With Smell Disorders Associated With COVID-19: Cross-Sectional Longitudinal Analysis Using Natural Language Processing of Self-Reports.

Nick S MengerArnaud TognettiMichael C FarruggiaCarla MucignatSurabhi BhutaniKeiland W CooperPaloma Paloma DomínguezThomas HeinbockelVonnie D C ShieldsAnna D'ErricoVeronica Pereda-CamposDenis PierronSachiko KoyamaIlja Croijmans
Published in: JMIR public health and surveillance (2024)
Our work shows consistent findings with those of previous studies, which indicate that self-reports, which can easily be extracted online, may offer valuable information to health care and understanding of smell disorders. At the same time, our study on self-reports provides new insights for future studies investigating smell disorders.
Keyphrases
  • cross sectional
  • healthcare
  • adverse drug
  • coronavirus disease
  • sars cov
  • health information
  • social media
  • case control
  • emergency department
  • current status
  • electronic health record