Whole-tumor histogram analysis of apparent diffusion coefficient maps with machine learning algorithms for predicting histologic grade of sinonasal squamous cell carcinoma: a preliminary study-Reference-Cited by-同舟云学术

Whole-tumor histogram analysis of apparent diffusion coefficient maps with machine learning algorithms for predicting histologic grade of sinonasal squamous cell carcinoma: a preliminary study

Published:2023-05-09 Issue:9 Volume:280 Page:4131-4140
ISSN:0937-4477
Container-title:European Archives of Oto-Rhino-Laryngology
language:en
Short-container-title:Eur Arch Otorhinolaryngol

Author:

Geng Yue^ORCID,Hong Rujian,Cheng Yushu,Zhang Fang,Sha Yan,Song Yang

Publisher

Springer Science and Business Media LLC

Subject

General Medicine,Otorhinolaryngology

Link

https://link.springer.com/content/pdf/10.1007/s00405-023-07989-9.pdf

Reference30 articles.

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2. Quan H, Yan L, Zhang H et al (2019) Development and validation of a nomogram for prognosis of sinonasal squamous cell carcinoma. Int Forum Allergy Rhinol 9:1030–1040. https://doi.org/10.1002/alr.22354

3. Roland NJ, Caslin AW, Nash J et al (1992) Value of grading squamous cell carcinoma of the head and neck. Head Neck 14:224–229. https://doi.org/10.1002/hed.2880140310

4. Larsen SR, Johansen J, Sørensen JA et al (2009) The prognostic significance of histological features in oral squamous cell carcinoma. J Oral Pathol Med 38:657–662. https://doi.org/10.1111/j.1600-0714.2009.00797.x

5. Ackall FY, Issa K, Barak I et al (2021) Survival outcomes in sinonasal poorly differentiated squamous cell carcinoma. Laryngoscope 131:E1040–E1048. https://doi.org/10.1002/lary.29090

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