Back to search

Article

ACRnet: Adaptive Cross-transfer Residual neural network for chest X-ray images discrimination

2021-11-02

Abstract excerpt

<h4>Background: </h4> Cardiothoracic diseases are a serious threat to human health and chest X-ray images have great reference value for the diagnosis and treatment. However, it is difficult for professional doctors to accurately diagnose cardiothoracic diseases through chest X-ray images sometimes and there will be different understanding based on human subjective differences, which will affect the judgment and t...

Topics

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

Identifiers and source

Literature Corpus work
74aea3c3-246c-59d8-abe9-9461d4d5892e
DOI
10.21203/rs.3.rs-1015912/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.
ACRnet: Adaptive Cross-transfer Residual neural network for chest X-ray images discriminationDOI 10.21203/rs.3.rs-1015912/v1
Select a neighboring publication to make it the new centre.