Deep learning for spirometry quality assurance with spirometric indices and curves

HIGHLIGHTS

• who: Yimin Wang from the The present study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (approval number:, )Since it was an anonymized and retrospective research, written informed consent was waived. have published the Article: Deep learning for spirometry quality assurance with spirometric indices and curves, in the Journal: (JOURNAL)
• what: The authors aimed to develop a high accuracy and sensitive deep learning-based model aiming at assisting high-quality spirometry assurance. Comparing to previous literature, the authors aimed to develop a more advanced approach in this work . . .
  

   

  

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