132 related articles for article (PubMed ID: 34510879)
1. [Diagnostic efficacy of a combined diagnostic model based on extreme gradient boosting algorithm in differentiating the pathological grading of gastric neuroendocrine neoplasms].
Wang R; Liang P; Yu J; Han YJ; Gao JB
Zhonghua Yi Xue Za Zhi; 2021 Sep; 101(34):2717-2722. PubMed ID: 34510879
[No Abstract] [Full Text] [Related]
2. [The value of spectral CT-based radiomics in preoperative prediction of lymph node metastasis of advanced gastric cancer].
Wang R; Li J; Fang MJ; Dong D; Liang P; Gao JB
Zhonghua Yi Xue Za Zhi; 2020 Jun; 100(21):1617-1622. PubMed ID: 32486595
[No Abstract] [Full Text] [Related]
3. Radiomics analysis of CT imaging for differentiating gastric neuroendocrine carcinomas from gastric adenocarcinomas.
Wang R; Liu H; Liang P; Zhao H; Li L; Gao J
Eur J Radiol; 2021 May; 138():109662. PubMed ID: 33774440
[TBL] [Abstract][Full Text] [Related]
4. Radiomics study for differentiating gastric cancer from gastric stromal tumor based on contrast-enhanced CT images.
Sun ZQ; Hu SD; Li J; Wang T; Duan SF; Wang J
J Xray Sci Technol; 2019; 27(6):1021-1031. PubMed ID: 31640109
[TBL] [Abstract][Full Text] [Related]
5. Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer.
Zhou Y; Su GY; Hu H; Ge YQ; Si Y; Shen MP; Xu XQ; Wu FY
Eur Radiol; 2020 Nov; 30(11):6251-6262. PubMed ID: 32500193
[TBL] [Abstract][Full Text] [Related]
6. Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning-based radiomics.
Mao B; Zhang L; Ning P; Ding F; Wu F; Lu G; Geng Y; Ma J
Eur Radiol; 2020 Dec; 30(12):6924-6932. PubMed ID: 32696256
[TBL] [Abstract][Full Text] [Related]
7. Application of Radiomics Analysis Based on CT Combined With Machine Learning in Diagnostic of Pancreatic Neuroendocrine Tumors Patient's Pathological Grades.
Zhang T; Zhang Y; Liu X; Xu H; Chen C; Zhou X; Liu Y; Ma X
Front Oncol; 2020; 10():521831. PubMed ID: 33643890
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. Correlation of four-phase CT findings of rectal neuroendocrine neoplasms with different World Health Organization grades.
Wang F; Wang J; Li Y; Wang X; Yu D; Zhang X
Abdom Radiol (NY); 2023 Mar; 48(3):855-864. PubMed ID: 36576516
[TBL] [Abstract][Full Text] [Related]
12. Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs): a radiomic model to predict tumor grade.
Chiti G; Grazzini G; Flammia F; Matteuzzi B; Tortoli P; Bettarini S; Pasqualini E; Granata V; Busoni S; Messserini L; Pradella S; Massi D; Miele V
Radiol Med; 2022 Sep; 127(9):928-938. PubMed ID: 35917099
[TBL] [Abstract][Full Text] [Related]
13. CT-based radiomics in predicting pathological response in non-small cell lung cancer patients receiving neoadjuvant immunotherapy.
Lin Q; Wu HJ; Song QS; Tang YK
Front Oncol; 2022; 12():937277. PubMed ID: 36267975
[TBL] [Abstract][Full Text] [Related]
14. A CT-based Radiomics Model for Prediction of Lymph Node Metastasis in Early Stage Gastric Cancer.
Gao X; Ma T; Cui J; Zhang Y; Wang L; Li H; Ye Z
Acad Radiol; 2021 Jun; 28(6):e155-e164. PubMed ID: 32507613
[TBL] [Abstract][Full Text] [Related]
15. Development and evaluation of a venous computed tomography radiomics model to predict lymph node metastasis from non-small cell lung cancer.
Cong M; Yao H; Liu H; Huang L; Shi G
Medicine (Baltimore); 2020 May; 99(18):e20074. PubMed ID: 32358390
[TBL] [Abstract][Full Text] [Related]
16. [Application of CT-based radiomics in differentiating primary gastric lymphoma from Borrmann type IV gastric cancer].
Deng J; Tan Y; Gu Q; Rong P; Wang W; Liu S
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2019 Mar; 44(3):257-263. PubMed ID: 30971517
[TBL] [Abstract][Full Text] [Related]
17. Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy.
Polk SL; Choi JW; McGettigan MJ; Rose T; Ahmed A; Kim J; Jiang K; Balagurunathan Y; Qi J; Farah PT; Rathi A; Permuth JB; Jeong D
World J Gastroenterol; 2020 Jun; 26(24):3458-3471. PubMed ID: 32655269
[TBL] [Abstract][Full Text] [Related]
18. A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors.
Ye JY; Fang P; Peng ZP; Huang XT; Xie JZ; Yin XY
Eur Radiol; 2024 Mar; 34(3):1994-2005. PubMed ID: 37658884
[TBL] [Abstract][Full Text] [Related]
19. Potential value of CT radiomics in the distinction of intestinal-type gastric adenocarcinomas.
Wang Y; Liu W; Yu Y; Han W; Liu JJ; Xue HD; Lei J; Jin ZY; Yu JC
Eur Radiol; 2020 May; 30(5):2934-2944. PubMed ID: 32020404
[TBL] [Abstract][Full Text] [Related]
20. Pancreatic neuroendocrine tumors containing areas of iso- or hypoattenuation in dynamic contrast-enhanced computed tomography: Spectrum of imaging findings and pathological grading.
Hyodo R; Suzuki K; Ogawa H; Komada T; Naganawa S
Eur J Radiol; 2015 Nov; 84(11):2103-9. PubMed ID: 26321494
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]