Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers’ performance and final diagnosis

PURPOSE: To evaluate the performance of a deep learning-based computer-aided detection (CAD) software for detecting pulmonary nodules, masses, and consolidation on chest radiographs (CRs) and to examine the effect of readers’ experience and data characteristics on the sensitivity and final diagnosis...

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Detalles Bibliográficos
Autores principales: Toda, Naoki, Hashimoto, Masahiro, Iwabuchi, Yu, Nagasaka, Misa, Takeshita, Ryo, Yamada, Minoru, Yamada, Yoshitake, Jinzaki, Masahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813234/
https://www.ncbi.nlm.nih.gov/pubmed/36121622
http://dx.doi.org/10.1007/s11604-022-01330-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813234/
https://www.ncbi.nlm.nih.gov/pubmed/36121622
http://dx.doi.org/10.1007/s11604-022-01330-w

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