Feature Tokenizer-Transformers with Self-Training for The Prediction of PD-L1 Expression of Non-Small Cell Lung Cancer from CT-Reference-Cited by-同舟云学术

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Feature Tokenizer-Transformers with Self-Training for The Prediction of PD-L1 Expression of Non-Small Cell Lung Cancer from CT

Published:2024-05-27 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Saber Ralph¹,Tonneau Marion¹,Bahig Sami²,Malo Julie²,Belkaid Wiam²,Messaoudene Meriem²,Bouchard Nicole³,Coulombe François⁴,Joubert Philippe⁴,Bahig Houda²,Turcotte Simon²,Routy Bertrand²,Kadoury Samuel¹

Affiliation:

1. Polytechnique Montréal,MedICAL Laboratory,Montréal, Québec,Canada

2. Centre de Recherche du CHUM,Montréal, Québec,Canada

3. Centre Hospitalier Universitaire de Sherbrooke,Québec,Canada

4. Institut Universitaire de Cardiologie et de Pneumologie de Québec,Québec,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635812.pdf?arnumber=10635812

Reference22 articles.

1. Toward personalized treatment approaches for non-small-cell lung cancer

2. Epidemiology of lung cancer

3. Five-Year Outcomes With Pembrolizumab Versus Chemotherapy for Metastatic Non–Small-Cell Lung Cancer With PD-L1 Tumor Proportion Score ≥ 50%

4. Precision Medicine for NSCLC in the Era of Immunotherapy: New Biomarkers to Select the Most Suitable Treatment or the Most Suitable Patient

5. Nivolumab plus Ipilimumab in Advanced Non–Small-Cell Lung Cancer

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