Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram-Reference-Cited by-同舟云学术

Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram

Published:2022-04-02 Issue:9 Volume:32 Page:6196-6206
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Zhong Jingyu^ORCID,Zhang Chengxiu,Hu Yangfan,Zhang Jing,Liu Yun,Si Liping,Xing Yue,Ding Defang,Geng Jia,Jiao Qiong,Zhang Huizhen,Yang Guang,Yao Weiwu

Funder

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Shanghai Jiao Tong University

School of Medicine, Shanghai Jiao Tong University

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-022-08735-1.pdf

Reference39 articles.

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2. Whelan JS, Davis LE (2018) Osteosarcoma, chondrosarcoma, and chordoma. J Clin Oncol 36(2):188–193

3. Strauss SJ, Frezza AM, Abecassis N et al (2021) Bone sarcomas: ESMO-EURACAN-GENTURIS-ERN PaedCan clinical practice guideline for diagnosis, treatment and follow-up. Ann Oncol 32(12):1520–1536

4. National Comprehensive Cancer Network (2020) NCCN clinical practice guidelines in oncology: Bone Cancer, v1.2021. Available via https://www.nccn.org/professionals/physician_gls/pdf/bone.pdf. Accessed November 2021

5. Xin S, Wei G (2020) Prognostic factors in osteosarcoma: a study level meta-analysis and systematic review of current practice. J Bone Oncol 21:100281

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