/CBMS-DL-based-radiomics

Paper published in the 36th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS 2023)

Primary LanguageJupyter NotebookMIT LicenseMIT

CBMS-DL-based-radiomics

This repository contains the code used in A Deep Learning-based Radiomics for COVID-19 Detection from CXR images using Ensemble Learning Model

Authors: Márcus V. L. Costa, Erikson J. de Aguiar, Lucas S. Rodrigues, Jonathan S. Ramos, Caetano Traina Jr. and Agma J. M. Traina

Summary: [Paper] [Dataset] [Results] [BibTeX] [Contact]

Conference

The 36th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS2023) will be held at the University of L’Aquila, L’Aquila, Italy, from Thursday 22th to Saturday 24th of June 2023.

Proposed Overview

Fig.1: Workflow employed in this study.

Results

More results and details.

Citing us

@inproceedings{CostaMVL2023,
  author={Costa, Márcus V. L. and de Aguiar, Erikson J. and Rodrigues, Lucas S. and Ramos, Jonathan S. and Traina, Caetano and Traina, Agma J. M.},
  booktitle={2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)}, 
  title={A {D}eep {L}earning-based {R}adiomics {A}pproach for {COVID-19} {D}etection from {CXR} {I}mages using {E}nsemble {L}earning {M}odel}, 
  year={2023},
  volume={},
  number={},
  pages={517-522},
  doi={10.1109/CBMS58004.2023.00272}
}

Contact

This work is part of my program Master's degree. You can contact me writing to marcusvlc@usp.br or LinkedIn.