Publication

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma

Jiancheng Yang, Li Zhang, Lin Chen, Qiong Li, Ying Zhu
2023
Journal Articles

Abstract

Objectives To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements.

Official source

https://infoscience.epfl.ch/entities/publication/19407dbe-3c1c-417b-9117-800b090c1e6d

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Jiancheng Yang, Li Zhang, Lin Chen, Qiong Li, Ying Zhu
2023
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/19407dbe-3c1c-417b-9117-800b090c1e6d

About this result

Related concepts (22)

Cancer staging

Cancer staging is the process of determining the extent to which a cancer has grown and spread. A number from I to IV is assigned, with I being an isolated cancer and IV being a cancer that has metastasized and spread from its origin. The stage generally takes into account the size of a tumor, whether it has invaded adjacent organs, how many regional (nearby) lymph nodes it has spread to (if any), and whether it has appeared in more distant locations (metastasized).

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Deep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.

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Breast cancer classification divides breast cancer into categories according to different schemes criteria and serving a different purpose. The major categories are the histopathological type, the grade of the tumor, the stage of the tumor, and the expression of proteins and genes. As knowledge of cancer cell biology develops these classifications are updated. The purpose of classification is to select the best treatment. The effectiveness of a specific treatment is demonstrated for a specific breast cancer (usually by randomized, controlled trials).

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