Automatic image segmentation and online survival prediction model of medulloblastoma based on machine learning-Reference-Cited by-同舟云学术

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Automatic image segmentation and online survival prediction model of medulloblastoma based on machine learning

Published:2023-11-23 Issue: Volume: Page:
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Zhou Lili,Ji Qiang,Peng Hong,Chen Feng,Zheng Yi,Jiao Zishan,Gong Jian,Li Wenbin^ORCID

Funder

Key Technology Research and Development Program of Shandong

National Major Science and Technology Projects of China

Clinical Major Specialty Projects of Beijing

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-023-10316-9.pdf

Reference47 articles.

1. Waszak SM, Northcott PA, Buchhalter I et al (2018) Spectrum and prevalence of genetic predisposition in medulloblastoma: a retrospective genetic study and prospective validation in a clinical trial cohort. Lancet Oncol 19:785–798

2. Kocakaya S, Beier CP, Beier D (2016) Chemotherapy increases long-term survival in patients with adult medulloblastoma–a literature-based meta-analysis. Neuro Oncol 18:408–416

3. Ray S, Chaturvedi NK, Bhakat KK, Rizzino A, Mahapatra S (2021) Subgroup-specific diagnostic, prognostic, and predictive markers influencing pediatric medulloblastoma treatment. Diagnostics 12:61–85

4. Riffaud L, Saikali S, Leray E et al (2009) Survival and prognostic factors in a series of adults with medulloblastomas. J Neurosurg 111:478–487

5. Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577

Cited by 3 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. Deep learning models for predicting the survival of patients with medulloblastoma based on a surveillance, epidemiology, and end results analysis;Scientific Reports;2024-06-24

2. A Radiomic Approach for Evaluating Intra-Subgroup Heterogeneity in SHH and Group 4 Pediatric Medulloblastoma: A Preliminary Multi-Institutional Study;Cancers;2024-06-18

3. Deep learning models for predicting the survival of patients with medulloblastoma based on a surveillance, epidemiology, and end results analysis;2024-03-08

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