Explainable Machine Learning for the Diagnosis of Aggressive Glioma with Amino Acid PET Imaging: Multicentric Clinical Validation-Reference-Cited by-同舟云学术

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Explainable Machine Learning for the Diagnosis of Aggressive Glioma with Amino Acid PET Imaging: Multicentric Clinical Validation

Published:2024 Issue: Volume: Page:
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Author:

Ahrari Shamimeh,Zaragori Timothée,Zinsz Adeline,Hossu Gabriela,Oster Julien,Allard Bastien,Al Mansour Laure,Bessac Darejan,Boumedine Sami,Bund Caroline,De Leiris Nicolas,Flaus Anthime,Guedj Eric,Kas Aurélie,Keromnes Nathalie,Kiraz Kevin,Kuijper Fiene Marie,Maitre Valentine,Querellou Solène,Stien Guilhem,Humbert Olivier,Imbert Laetitia,Verger Antoine

Publisher

Elsevier BV

Reference39 articles.

1. Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas;N L Albert;Neuro-Oncology,2016

2. Role of amino acid PET in HGGs: limitations and perspectives;A Verger;Quarterly Journal of Nuclear Medicine and Molecular Imaging,2018

3. Radiomics in neuro-oncological clinical trials;P Lohmann;The Lancet Digital Health,2022

4. Explainable Deep Learning Improves Physician Interpretation of Myocardial Perfusion Imaging;R J H Miller;J Nucl Med jnumed,2022

5. An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph;H H Pham;IEEE Access,2022

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