[Performance of multi-modality and multi-classifier fusion models for predicting radiation-induced oral mucositis in patients with nasopharyngeal carcinoma].

Compared with each of the individual classifiers, the multimodal multi-classifier fusion algorithm combining clinical and dosimetric modalities demonstrates superior performance in predicting the incidence of severe RIOM in NPC patients following radiotherapy.

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Publication Details

Journal
PubMed
Published
2024-12-20
DOI
https://doi.org/10.12122/j.issn.1673-4254.2024.12.20
Citations
1
Primary Topic
Head and Neck Cancer Studies
Type
article
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article

[Performance of multi-modality and multi-classifier fusion models for predicting radiation-induced oral mucositis in patients with nasopharyngeal carcinoma].

Linjing Wang, Xin Zhen, Pan Gong, Ming Jen Tan et al.
1 citations
PubMed
Head and Neck Cancer Studies
article

[Performance of multi-modality and multi-classifier fusion models for predicting radiation-induced oral mucositis in patients with nasopharyngeal carcinoma].

Linjing Wang, Xin Zhen, Pan Gong, Ming Jen Tan, Bin Qi, Yu Zeng, Zhiwei Liao, Yue Hu, Yanhao Kuang
article en
1 citations

Abstract

Compared with each of the individual classifiers, the multimodal multi-classifier fusion algorithm combining clinical and dosimetric modalities demonstrates superior performance in predicting the incidence of severe RIOM in NPC patients following radiotherapy.

PubMedVol. 44(12)
Southern Medical University (CN)
Head and Neck Cancer Studies
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