An Artificial Intelligence–Driven Preoperative Radiomic Subtype for Predicting the Prognosis and Treatment Response of Patients with Papillary Thyroid Carcinoma

DLRI is a reliable noninvasive tool for evaluating prognosis and guiding anti-inflammatory TCM treatment in patients with PTC. Prospective studies are needed to confirm these findings.

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Publication Details

Journal
Clinical Cancer Research
Published
2024-11-13
DOI
https://doi.org/10.1158/1078-0432.ccr-24-2356
Citations
5
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
2.02

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article

An Artificial Intelligence–Driven Preoperative Radiomic Subtype for Predicting the Prognosis and Treatment Response of Patients with Papillary Thyroid Carcinoma

Ming Gao, Xiangqian Zheng, Huan Zhang, Biyun Qian et al.
5 citations
Clinical Cancer Research
Radiomics and Machine Learning in Medical Imaging
2.02
article

An Artificial Intelligence–Driven Preoperative Radiomic Subtype for Predicting the Prognosis and Treatment Response of Patients with Papillary Thyroid Carcinoma

Ming Gao, Xiangqian Zheng, Huan Zhang, Biyun Qian, Yu Wang, Weituo Zhang, Tian Liao, Xinwei Yun, Herbert Yu, Dapeng Li, Qiang Li, Yanzhi Zhang, Ning Qu, Ben Ma, Yi Gao, Jingzhu Zhao, Anqi Jin
article en
5 citations

Abstract

DLRI is a reliable noninvasive tool for evaluating prognosis and guiding anti-inflammatory TCM treatment in patients with PTC. Prospective studies are needed to confirm these findings.

Clinical Cancer ResearchVol. 31(1)
University of Hawaiʻi at Mānoa (US), City Of Hope National Medical Center (US), University of Hawaii System (US), Shanghai Jiao Tong University (CN), Tianjin Medical University General Hospital (CN), Tianjin Medical University Cancer Institute and Hospital (CN), Fudan University Shanghai Cancer Center (CN), Cancer Center of Hawaii (US), Tongren Hospital (CN), Shanghai Tenth People's Hospital (CN), University of Hawaii Cancer Center, Tianjin Medical University (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality
No poverty
Openalex Percentile: Top 13%
Radiomics and Machine Learning in Medical Imaging
2.02
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