A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma

A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma

Abstract This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung adenocarcinoma (LUAD) based on its histopathological features. Clinicopathological data and whole slide images from 164 LUAD cases were collected and used to train DL models with an ImageNet pr...

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Bibliographic Details
Main Authors: Pil-Jong Kim, Hee Sang Hwang, Gyuheon Choi, Hyun-Jung Sung, Bokyung Ahn, Ji-Su Uh, Shinkyo Yoon, Deokhoon Kim, Sung-Min Chun, Se Jin Jang, Heounjeong Go
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
Deep learning
Lung adenocarcinoma
Recurrence
Histopathology
Pathology image
Online Access:https://doi.org/10.1038/s41598-024-56867-9

Internet

https://doi.org/10.1038/s41598-024-56867-9

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