Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis

We investigated the feasibility of a new deep-learning (DL)-based lung analysis method for the evaluation of interstitial lung disease (ILD) by comparing it with evaluation using the traditional computer-aided diagnosis (CAD) system and patients’ clinical outcomes. We prospectively included 104 pati...

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Detalles Bibliográficos
Autores principales: Aoki, Ryo, Iwasawa, Tae, Saka, Tomoki, Yamashiro, Tsuneo, Utsunomiya, Daisuke, Misumi, Toshihiro, Baba, Tomohisa, Ogura, Takashi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777463/
https://www.ncbi.nlm.nih.gov/pubmed/36553045
http://dx.doi.org/10.3390/diagnostics12123038

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777463/
https://www.ncbi.nlm.nih.gov/pubmed/36553045
http://dx.doi.org/10.3390/diagnostics12123038

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