CT-Based Radiomics Analysis of Different Machine Learning Models for Discriminating the Risk Stratification of Pheochromocytoma and Paraganglioma: A Multicenter Study-Reference-Cited by-同舟云学术

CT-Based Radiomics Analysis of Different Machine Learning Models for Discriminating the Risk Stratification of Pheochromocytoma and Paraganglioma: A Multicenter Study

Published:2024-07 Issue:7 Volume:31 Page:2859-2871
ISSN:1076-6332
Container-title:Academic Radiology
language:en
Short-container-title:Academic Radiology

Author:

Zhou Yongjie,Zhan Yuan,Zhao Jinhong,Zhong Linhua,Tan Yongming,Zeng Wei,Zeng Qiao,Gong Mingxian,Li Aihua,Gong Lianggeng,Liu Lan

Publisher

Elsevier BV

Reference32 articles.

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1. PheoSeg: A 3D transfer learning framework for accurate abdominal CT pheochromocytoma segmentation and surgical grade prediction;Knowledge-Based Systems;2024-10

2. SDH-related head and neck paragangliomas: Unraveling PET radiomics beyond 18F-FDG;Best Practice & Research Clinical Endocrinology & Metabolism;2024-08

3. The current and upcoming era of radiomics in phaeochromocytoma and paraganglioma;Best Practice & Research Clinical Endocrinology & Metabolism;2024-08