410 related articles for article (PubMed ID: 29667885)
1. Radiomics Approach to Prediction of Occult Mediastinal Lymph Node Metastasis of Lung Adenocarcinoma.
Zhong Y; Yuan M; Zhang T; Zhang YD; Li H; Yu TF
AJR Am J Roentgenol; 2018 Jul; 211(1):109-113. PubMed ID: 29667885
[TBL] [Abstract][Full Text] [Related]
2. Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?
Wang X; Zhao X; Li Q; Xia W; Peng Z; Zhang R; Li Q; Jian J; Wang W; Tang Y; Liu S; Gao X
Eur Radiol; 2019 Nov; 29(11):6049-6058. PubMed ID: 30887209
[TBL] [Abstract][Full Text] [Related]
3. Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.
Ma X; Xia L; Chen J; Wan W; Zhou W
Eur Radiol; 2023 Mar; 33(3):1949-1962. PubMed ID: 36169691
[TBL] [Abstract][Full Text] [Related]
4. Occult mediastinal lymph node metastasis in FDG-PET/CT node-negative lung adenocarcinoma patients: Risk factors and histopathological study.
Miao H; Shaolei L; Nan L; Yumei L; Shanyuan Z; Fangliang L; Yue Y
Thorac Cancer; 2019 Jun; 10(6):1453-1460. PubMed ID: 31127706
[TBL] [Abstract][Full Text] [Related]
5. Integrative nomogram of intratumoral, peritumoral, and lymph node radiomic features for prediction of lymph node metastasis in cT1N0M0 lung adenocarcinomas.
Das SK; Fang KW; Xu L; Li B; Zhang X; Yang HF
Sci Rep; 2021 May; 11(1):10829. PubMed ID: 34031529
[TBL] [Abstract][Full Text] [Related]
6. Comparison of a radiomic biomarker with volumetric analysis for decoding tumour phenotypes of lung adenocarcinoma with different disease-specific survival.
Yuan M; Zhang YD; Pu XH; Zhong Y; Li H; Wu JF; Yu TF
Eur Radiol; 2017 Nov; 27(11):4857-4865. PubMed ID: 28523350
[TBL] [Abstract][Full Text] [Related]
7. Biliary Tract Cancer at CT: A Radiomics-based Model to Predict Lymph Node Metastasis and Survival Outcomes.
Ji GW; Zhang YD; Zhang H; Zhu FP; Wang K; Xia YX; Zhang YD; Jiang WJ; Li XC; Wang XH
Radiology; 2019 Jan; 290(1):90-98. PubMed ID: 30325283
[TBL] [Abstract][Full Text] [Related]
8. A radiomics approach to predict lymph node metastasis and clinical outcome of intrahepatic cholangiocarcinoma.
Ji GW; Zhu FP; Zhang YD; Liu XS; Wu FY; Wang K; Xia YX; Zhang YD; Jiang WJ; Li XC; Wang XH
Eur Radiol; 2019 Jul; 29(7):3725-3735. PubMed ID: 30915561
[TBL] [Abstract][Full Text] [Related]
9. Predictive value of radiomic features extracted from primary lung adenocarcinoma in forecasting thoracic lymph node metastasis: a systematic review and meta-analysis.
Wu T; Gao C; Lou X; Wu J; Xu M; Wu L
BMC Pulm Med; 2024 May; 24(1):246. PubMed ID: 38762472
[TBL] [Abstract][Full Text] [Related]
10. Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: a pilot study.
Li K; Yao Q; Xiao J; Li M; Yang J; Hou W; Du M; Chen K; Qu Y; Li L; Li J; Wang X; Luo H; Yang J; Zhang Z; Chen W
Cancer Imaging; 2020 Jan; 20(1):12. PubMed ID: 32000852
[TBL] [Abstract][Full Text] [Related]
11. Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.
Zhan PC; Yang T; Zhang Y; Liu KY; Li Z; Zhang YY; Liu X; Liu NN; Wang HX; Shang B; Chen Y; Jiang HY; Zhao XT; Shao JH; Chen Z; Wang XD; Wang K; Gao JB; Lyu PJ
Eur Radiol; 2024 Feb; 34(2):1280-1291. PubMed ID: 37589900
[TBL] [Abstract][Full Text] [Related]
12. A deep learning-based radiomics model for predicting lymph node status from lung adenocarcinoma.
Xie H; Song C; Jian L; Guo Y; Li M; Luo J; Li Q; Tan T
BMC Med Imaging; 2024 May; 24(1):121. PubMed ID: 38789936
[TBL] [Abstract][Full Text] [Related]
13. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.
Jiang C; Luo Y; Yuan J; You S; Chen Z; Wu M; Wang G; Gong J
Eur Radiol; 2020 Jul; 30(7):4050-4057. PubMed ID: 32112116
[TBL] [Abstract][Full Text] [Related]
14. Prediction of pathological nodal involvement by CT-based Radiomic features of the primary tumor in patients with clinically node-negative peripheral lung adenocarcinomas.
Liu Y; Kim J; Balagurunathan Y; Hawkins S; Stringfield O; Schabath MB; Li Q; Qu F; Liu S; Garcia AL; Ye Z; Gillies RJ
Med Phys; 2018 Jun; 45(6):2518-2526. PubMed ID: 29624702
[TBL] [Abstract][Full Text] [Related]
15. [Application of a Radiomics Model for Preding Lymph Node Metastasis in Non-small Cell Lung Cancer].
Zhu J; Xu WG; Xiao H; Zhou Y
Sichuan Da Xue Xue Bao Yi Xue Ban; 2019 May; 50(3):373-378. PubMed ID: 31631606
[TBL] [Abstract][Full Text] [Related]
16. Applying a radiomics-based strategy to preoperatively predict lymph node metastasis in the resectable pancreatic ductal adenocarcinoma.
Liu P; Gu Q; Hu X; Tan X; Liu J; Xie A; Huang F
J Xray Sci Technol; 2020; 28(6):1113-1121. PubMed ID: 33074215
[TBL] [Abstract][Full Text] [Related]
17. CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.
Wang Y; Liu W; Yu Y; Liu JJ; Xue HD; Qi YF; Lei J; Yu JC; Jin ZY
Eur Radiol; 2020 Feb; 30(2):976-986. PubMed ID: 31468157
[TBL] [Abstract][Full Text] [Related]
18. Radiomics nomogram outperforms size criteria in discriminating lymph node metastasis in resectable esophageal squamous cell carcinoma.
Tan X; Ma Z; Yan L; Ye W; Liu Z; Liang C
Eur Radiol; 2019 Jan; 29(1):392-400. PubMed ID: 29922924
[TBL] [Abstract][Full Text] [Related]
19. A radiomics-based model for prediction of lymph node metastasis in gastric cancer.
Gao X; Ma T; Cui J; Zhang Y; Wang L; Li H; Ye Z
Eur J Radiol; 2020 Aug; 129():109069. PubMed ID: 32464581
[TBL] [Abstract][Full Text] [Related]
20. Radiomics analysis using contrast-enhanced CT for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer.
Liu S; He J; Liu S; Ji C; Guan W; Chen L; Guan Y; Yang X; Zhou Z
Eur Radiol; 2020 Jan; 30(1):239-246. PubMed ID: 31385045
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]