Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease

BACKGROUND: Currently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow obstruction. We hypothesized that machine-learning algorithms can be trained on spirometry data to identify these structural phenotypes. METHODS: Part...

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Bibliografische gegevens
Gepubliceerd in:JCI Insight
Hoofdauteurs: Bodduluri, Sandeep, Nakhmani, Arie, Reinhardt, Joseph M., Wilson, Carla G., McDonald, Merry-Lynn, Rudraraju, Ramaraju, Jaeger, Byron C., Bhakta, Nirav R., Castaldi, Peter J., Sciurba, Frank C., Zhang, Chengcui, Bangalore, Purushotham V., Bhatt, Surya P.
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: American Society for Clinical Investigation 2020
Onderwerpen:
Clinical Medicine
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7406302/
https://ncbi.nlm.nih.gov/pubmed/32554922
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1172/jci.insight.132781
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