Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features.
文献类型：期刊论文
| 作者 | Zheng, Hairong; Li, Weimin; Tian, Jie; Zhou, Hongyu; Dong, Di; Chen, Bojiang; Fang, Mengjie; Cheng, Yue; Gan, Yuncun; Zhang, Rui |
| 刊名 | TRANSLATIONAL ONCOLOGY
 |
| 出版日期 | 2018 |
| 文献子类 | 期刊论文 |
| 英文摘要 | OBJECTIVES: To analyze the distant metastasis possibility based on computed tomography (CT) radiomic features in patients with lung cancer. METHODS: This was a retrospective analysis of 348 patients with lung cancer enrolled between 2014 and February 2015. A feature set containing clinicalfeatures and 485 radiomic features was extracted from the pretherapy CT images. Feature selection via concave minimization (FSV) was used to select effective features. A support vector machine (SVM) was used to evaluate the predictive ability of each feature. RESULTS: Four radiomic features and three clinical features were obtained by FSV feature selection. Classification accuracy by the proposed SVM with SGD method was 71.02%, and the area under the curve was 72.84% with only the radiomicfeatures extracted from CT. After the addition of clinical features, 89.09% can be achieved. CONCLUSION: The radiomic features of the pretherapy CT images may be used as predictors ofdistant metastasis. And it also can be used in combination with the patient's gender and tumor T and N phase information to diagnose the possibility of distant metastasis in lung cancer. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14307]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 推荐引用方式 GB/T 7714 | Zheng, Hairong,Li, Weimin,Tian, Jie,et al. Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features.[J]. TRANSLATIONAL ONCOLOGY,2018. |
| APA | Zheng, Hairong.,Li, Weimin.,Tian, Jie.,Zhou, Hongyu.,Dong, Di.,...&Liu, Zhenyu.(2018).Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features..TRANSLATIONAL ONCOLOGY. |
| MLA | Zheng, Hairong,et al."Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features.".TRANSLATIONAL ONCOLOGY (2018). |
入库方式： OAI收割
来源：深圳先进技术研究院
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