Machine Learning-Based MRI Radiogenomics for Evaluation of Response to Induction Chemotherapy in Head and Neck Squamous Cell Carcinoma
Author:
Publisher
Elsevier BV
Subject
Radiology, Nuclear Medicine and imaging
Reference25 articles.
1. Head and neck squamous cell carcinoma;Johnson;Nat Rev Dis Primers,2020
2. Relevance of apparent diffusion coefficient features for a radiomics-based prediction of response to induction chemotherapy in sinonasal cancer;Bologna;NMR Biomed,2022
3. Automated prediction of early recurrence in advanced sinonasal squamous cell carcinoma with deep learning and multi-parametric MRI-based radiomics nomogram;Lin;Acad Radiol,2023
4. CT-based radiomics signature analysis for evaluation of response to induction chemotherapy and progression-free survival in locally advanced hypopharyngeal carcinoma;Liu;Eur Radiol,2022
5. Intravoxel incoherent motion magnetic resonance imaging for prediction of induction chemotherapy response in locally advanced hypopharyngeal carcinoma: comparison with model-free dynamic contrast-enhanced magnetic resonance imaging;Guo;J Magn Reson Imaging,2021
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Radiogenomics is Elevating Treatment Response Prediction in Head and Neck Squamous Cell Carcinoma;Academic Radiology;2024-06
2. Prediction of pathological complete response in locally advanced head and neck squamous cell carcinoma treated with neoadjuvant chemo-immunotherapy using volumetric multisequence MRI histogram analysis;Neuroradiology;2024-03-20
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