Prediction of oxygen supplementation by a deep-learning model integrating clinical parameters and chest CT images in COVID-19

PURPOSE: As of March 2023, the number of patients with COVID-19 worldwide is declining, but the early diagnosis of patients requiring inpatient treatment and the appropriate allocation of limited healthcare resources remain unresolved issues. In this study we constructed a deep-learning (DL) model t...

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Detalles Bibliográficos
Autores principales: Kawata, Naoko, Iwao, Yuma, Matsuura, Yukiko, Suzuki, Masaki, Ema, Ryogo, Sekiguchi, Yuki, Sato, Hirotaka, Nishiyama, Akira, Nagayoshi, Masaru, Takiguchi, Yasuo, Suzuki, Takuji, Haneishi, Hideaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687147/
https://www.ncbi.nlm.nih.gov/pubmed/37440160
http://dx.doi.org/10.1007/s11604-023-01466-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687147/
https://www.ncbi.nlm.nih.gov/pubmed/37440160
http://dx.doi.org/10.1007/s11604-023-01466-3

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