Editorial for "MRI-Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma"
- PMID: 34962010
- DOI: 10.1002/jmri.28049
Editorial for "MRI-Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma"
Comment on
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MRI-Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma.J Magn Reson Imaging. 2022 Aug;56(2):547-559. doi: 10.1002/jmri.28047. Epub 2021 Dec 30. J Magn Reson Imaging. 2022. PMID: 34970824
References
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- Mane M, Benkhaled S, Dragan T, et al. Meta-analysis on induction chemotherapy in locally advanced nasopharyngeal carcinoma. Oncologist 2021;26(1):e130-e141.
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- Jansen JFA, Parra C, Lu Y, Shukla-Dave A. Evaluation of head and neck tumors with functional MR imaging. Magn Reson Imaging Clin N Am 2016;24(1):123-133.
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- Jansen JF, Lu Y, Gupta G, et al. Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer. World J Radiol 2016;8(1):90-97.
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- Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: Extracting more information from medical images using advanced feature analysis. Eur J Cancer 2012;48(4):441-446.
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- Yongfeng P, Chuner J, Lei W, et al. The usefulness of pretreatment MR-based radiomics on early response of neoadjuvant chemotherapy in patients with locally advanced nasopharyngeal carcinoma. Oncol Res 2021;28(6):605-613.
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