A Self-Attention Based Fusion Model of Radiomics and Deep Features for Early Recurrence Prediction in NSCLC
Author:
Affiliation:
1. Ritsumeikan University,Graduate School of Information Science and Engineering,Shiga,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10315246/10315146/10315672.pdf?arnumber=10315672
Reference14 articles.
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3. The Regression Analysis of Binary Sequences
4. Importance of CT image normalization in radiomics analysis: prediction of 3-year recurrence-free survival in non-small cell lung cancer
5. A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models
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