109 related articles for article (PubMed ID: 38013377)
21. A novel radiomic nomogram for predicting epidermal growth factor receptor mutation in peripheral lung adenocarcinoma.
Lu X; Li M; Zhang H; Hua S; Meng F; Yang H; Li X; Cao D
Phys Med Biol; 2020 Mar; 65(5):055012. PubMed ID: 31978901
[TBL] [Abstract][Full Text] [Related]
22. Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.
Shu J; Wen D; Xi Y; Xia Y; Cai Z; Xu W; Meng X; Liu B; Yin H
Eur J Radiol; 2019 Dec; 121():108738. PubMed ID: 31756634
[TBL] [Abstract][Full Text] [Related]
23. Radiomics study for predicting the expression of PD-L1 in non-small cell lung cancer based on CT images and clinicopathologic features.
Sun Z; Hu S; Ge Y; Wang J; Duan S; Song J; Hu C; Li Y
J Xray Sci Technol; 2020; 28(3):449-459. PubMed ID: 32176676
[TBL] [Abstract][Full Text] [Related]
24. Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.
Yin P; Mao N; Zhao C; Wu J; Sun C; Chen L; Hong N
Eur Radiol; 2019 Apr; 29(4):1841-1847. PubMed ID: 30280245
[TBL] [Abstract][Full Text] [Related]
25. A CT-based radiomics nomogram for differentiation of renal angiomyolipoma without visible fat from homogeneous clear cell renal cell carcinoma.
Nie P; Yang G; Wang Z; Yan L; Miao W; Hao D; Wu J; Zhao Y; Gong A; Cui J; Jia Y; Niu H
Eur Radiol; 2020 Feb; 30(2):1274-1284. PubMed ID: 31506816
[TBL] [Abstract][Full Text] [Related]
26. Radiomics Nomogram Based on Contrast-enhanced CT to Predict the Malignant Potential of Gastrointestinal Stromal Tumor: A Two-center Study.
Song Y; Li J; Wang H; Liu B; Yuan C; Liu H; Zheng Z; Min F; Li Y
Acad Radiol; 2022 Jun; 29(6):806-816. PubMed ID: 34238656
[TBL] [Abstract][Full Text] [Related]
27. Development of a predictive radiomics model for lymph node metastases in pre-surgical CT-based stage IA non-small cell lung cancer.
Cong M; Feng H; Ren JL; Xu Q; Cong L; Hou Z; Wang YY; Shi G
Lung Cancer; 2020 Jan; 139():73-79. PubMed ID: 31743889
[TBL] [Abstract][Full Text] [Related]
28. Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma.
He H; Jin Z; Dai J; Wang H; Sun J; Xu D
Cancer Med; 2023 Mar; 12(6):7627-7638. PubMed ID: 36397666
[TBL] [Abstract][Full Text] [Related]
29. CT-based multi-phase Radiomic models for differentiating clear cell renal cell carcinoma.
Chen M; Yin F; Yu Y; Zhang H; Wen G
Cancer Imaging; 2021 Jun; 21(1):42. PubMed ID: 34162442
[TBL] [Abstract][Full Text] [Related]
30. Discrimination of mediastinal metastatic lymph nodes in NSCLC based on radiomic features in different phases of CT imaging.
Sha X; Gong G; Qiu Q; Duan J; Li D; Yin Y
BMC Med Imaging; 2020 Feb; 20(1):12. PubMed ID: 32024469
[TBL] [Abstract][Full Text] [Related]
31. A CT-based radiomics model for predicting renal capsule invasion in renal cell carcinoma.
Yang L; Gao L; Arefan D; Tan Y; Dan H; Zhang J
BMC Med Imaging; 2022 Jan; 22(1):15. PubMed ID: 35094674
[TBL] [Abstract][Full Text] [Related]
32. Differentiation of predominant subtypes of lung adenocarcinoma using a quantitative radiomics approach on CT.
Park S; Lee SM; Noh HN; Hwang HJ; Kim S; Do KH; Seo JB
Eur Radiol; 2020 Sep; 30(9):4883-4892. PubMed ID: 32300970
[TBL] [Abstract][Full Text] [Related]
33. CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors.
Zheng Y; Zhou D; Liu H; Wen M
Eur Radiol; 2022 Oct; 32(10):6953-6964. PubMed ID: 35484339
[TBL] [Abstract][Full Text] [Related]
34. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
[TBL] [Abstract][Full Text] [Related]
35. Differentiation of Lung Metastases Originated From Different Primary Tumors Using Radiomics Features Based on CT Imaging.
Shang H; Li J; Jiao T; Fang C; Li K; Yin D; Zeng Q
Acad Radiol; 2023 Jan; 30(1):40-46. PubMed ID: 35577699
[TBL] [Abstract][Full Text] [Related]
36. A Comprehensive Nomogram Combining CT Imaging with Clinical Features for Prediction of Lymph Node Metastasis in Stage I-IIIB Non-small Cell Lung Cancer.
Zheng X; Shao J; Zhou L; Wang L; Ge Y; Wang G; Feng F
Ther Innov Regul Sci; 2022 Jan; 56(1):155-167. PubMed ID: 34699046
[TBL] [Abstract][Full Text] [Related]
37. Evaluation of Radiomics Models Based on Computed Tomography for Distinguishing Between Benign and Malignant Thyroid Nodules.
Kong D; Zhang J; Shan W; Duan S; Guo L
J Comput Assist Tomogr; 2022 Nov-Dec 01; 46(6):978-985. PubMed ID: 35759774
[TBL] [Abstract][Full Text] [Related]
38. Prediction of osteoporosis using radiomics analysis derived from single source dual energy CT.
Wang J; Zhou S; Chen S; He Y; Gao H; Yan L; Hu X; Li P; Shen H; Luo M; You T; Li J; Zhong Z; Zhang K
BMC Musculoskelet Disord; 2023 Feb; 24(1):100. PubMed ID: 36750927
[TBL] [Abstract][Full Text] [Related]
39. Development and validation of a machine learning-derived radiomics model for diagnosis of osteoporosis and osteopenia using quantitative computed tomography.
Xie Q; Chen Y; Hu Y; Zeng F; Wang P; Xu L; Wu J; Li J; Zhu J; Xiang M; Zeng F
BMC Med Imaging; 2022 Aug; 22(1):140. PubMed ID: 35941568
[TBL] [Abstract][Full Text] [Related]
40. Predictive Value of CT-Based Radiomics in Distinguishing Renal Angiomyolipomas with Minimal Fat from Other Renal Tumors.
Han Z; Zhu Y; Xu J; Wen D; Xia Y; Zheng M; Yan T; Wei M
Dis Markers; 2022; 2022():9108129. PubMed ID: 35669501
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
