A novel explainable approach in radiomics pipeline for local recurrence prediction of lung cancer: a feasibility study exploiting high energy physics potential to evaluate the model-Reference-Cited by-同舟云学术

A novel explainable approach in radiomics pipeline for local recurrence prediction of lung cancer: a feasibility study exploiting high energy physics potential to evaluate the model

Published:2023-09-22 Issue: Volume: Page:184-187
ISSN:
Container-title:Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications
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Author:

Monteleone Mariagrazia¹^ORCID,Gennai Simone²^ORCID,Govoni Pietro³^ORCID,Paganelli Chiara¹^ORCID

Affiliation:

1. Dipartimento di Elettronica,Informazione e Bioingegneria, Politecnico di Milano, Italy

2. INFN sezione di Milano-Bicocca, Italy

3. Dipartimento di Fisica, Universita degli Studi di Milano Bicocca, Italy and INFN sezione di Milano-Bicocca, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3632047.3632074

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5. Shaimaa Bakr Olivier Gevaert Sebastian Echegaray Kelsey Ayers Mu Zhou Majid Shafiq Hong Zheng Weiruo Zhang Ann Leung Michael Kadoch 2017. Data for NSCLC Radiogenomics collection. The Cancer Imaging Archive.