Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
Cho et al. use a radiomics-guided deep-learning approach to model the prognosis of lung adenocarcinoma from CT scan data. This study demonstrates the utility of this technology as a predictive approach for stratifying clinical prognostic groups.
Guardado en:
Autores principales: | Hwan-ho Cho, Ho Yun Lee, Eunjin Kim, Geewon Lee, Jonghoon Kim, Junmo Kwon, Hyunjin Park |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/e3df764d36224d0dbccb596f1c5bbbad |
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