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Digitally recorded and remotely classified lung auscultation compared with conventional stethoscope classifications among children aged 1-59 months enrolled in the Pneumonia Etiology Research for Child Health (PERCH) case-control study.

Daniel E ParkNora L WatsonChristopher FochtDaniel FeikinLaura HammitW Abdullah BrooksStephen R C HowieKaren L KotloffOrin S LevineShabir A MadhiDavid R MurdochKatherine L O'BrienJ Anthony G ScottDonald M TheaTussanee AmorninthapichetJuliet AworiCharatdao BunthiBernard EbrukeMounya ElhilaliMelissa HigdonLokman HossainYasmin JahanDavid P MooreJustin MulindwaLawrence MwananyandaSathapana NaoratChristine ProsperiSomsak ThamthitiwatCharl VerweyKathleen A JablonskiMelinda C PowerHeather A YoungMaria Deloria KnollEric D McCollum
Published in: BMJ open respiratory research (2022)
Conventional auscultation and remotely-classified digital auscultation displayed moderate concordance for presence/absence of wheeze and crackles among cases. Conventional and digital auscultation may provide different classification patterns, but wheeze was associated with decreased clinical severity on both.
Keyphrases
  • machine learning
  • deep learning
  • high intensity
  • respiratory failure
  • extracorporeal membrane oxygenation
  • community acquired pneumonia