Cargando…
Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma
SIMPLE SUMMARY: The high-grade pattern (micropapillary or solid pattern, MPSol) in lung adenocarcinoma affects the patient’s poor prognosis. We aimed to develop a deep learning (DL) model for predicting any high-grade patterns in lung adenocarcinoma and to assess the prognostic performance of model...
Autores principales: | Choi, Yeonu, Aum, Jaehong, Lee, Se-Hoon, Kim, Hong-Kwan, Kim, Jhingook, Shin, Seunghwan, Jeong, Ji Yun, Ock, Chan-Young, Lee, Ho Yun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391458/ https://www.ncbi.nlm.nih.gov/pubmed/34439230 http://dx.doi.org/10.3390/cancers13164077 |
Ejemplares similares
-
Rethinking a Non-Predominant Pattern in Invasive Lung Adenocarcinoma: Prognostic Dissection Focusing on a High-Grade Pattern
por: Choi, Yeonu, et al.
Publicado: (2021) -
Tumor-infiltrating lymphocyte enrichment predicted by CT radiomics analysis is associated with clinical outcomes of non-small cell lung cancer patients receiving immune checkpoint inhibitors
por: Park, Changhee, et al.
Publicado: (2023) -
Pleomorphic carcinoma of the lung: Prognostic models of semantic, radiomics and combined features from CT and PET/CT in 85 patients
por: Kim, Chohee, et al.
Publicado: (2021) -
Pathologic heterogeneity of lung adenocarcinomas: A novel pathologic index predicts survival
por: Lee, Geewon, et al.
Publicado: (2016) -
Prognosis for Pneumonic-Type Invasive Mucinous Adenocarcinoma in a Single Lobe on CT: Is It Reasonable to Designate It as Clinical T3?
por: Kim, Wooil, et al.
Publicado: (2022)