Back to search

Article

Prediction of Tumor Spread Through Air Spaces with an Automatic Segmentation Deep Learning Model in Peripheral Stage I Lung Adenocarcinoma

2024-08-26

Abstract excerpt

<title>Abstract</title> <p><bold>Purpose:</bold> To evaluate the clinical applicability of deep learning (DL) models based on automatic segmentation in preoperatively predicting tumor spread through air spaces (STAS) in peripheral stage I lung adenocarcinoma (LUAD). <bold>Methods:</bold> This retrospective study analyzed data from patients who underwent surgical treatment for lung tumors from January 2022 to Dece...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
0f7e0168-2cf9-5d87-9e3a-aa0b39aa4fb4
DOI
10.21203/rs.3.rs-4768392/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Prediction of Tumor Spread Through Air Spaces with an Automatic Segmentation Deep Learning Model in Peripheral Stage I Lung AdenocarcinomaDOI 10.21203/rs.3.rs-4768392/v1
Select a neighboring publication to make it the new centre.