233 related articles for article (PubMed ID: 34103619)
1. Value of radiomics model based on enhanced computed tomography in risk grade prediction of gastrointestinal stromal tumors.
Chu H; Pang P; He J; Zhang D; Zhang M; Qiu Y; Li X; Lei P; Fan B; Xu R
Sci Rep; 2021 Jun; 11(1):12009. PubMed ID: 34103619
[TBL] [Abstract][Full Text] [Related]
2. Predictive Value of a Radiomics Nomogram Model Based on Contrast-Enhanced Computed Tomography for KIT Exon 9 Gene Mutation in Gastrointestinal Stromal Tumors.
Wei Y; Lu Z; Ren Y
Technol Cancer Res Treat; 2023; 22():15330338231181260. PubMed ID: 37296525
[TBL] [Abstract][Full Text] [Related]
3. Development and validation of a nomogram based on CT images and 3D texture analysis for preoperative prediction of the malignant potential in gastrointestinal stromal tumors.
Ren C; Wang S; Zhang S
Cancer Imaging; 2020 Jan; 20(1):5. PubMed ID: 31931874
[TBL] [Abstract][Full Text] [Related]
4. Combined model based on enhanced CT texture features in liver metastasis prediction of high-risk gastrointestinal stromal tumors.
Zheng J; Xia Y; Xu A; Weng X; Wang X; Jiang H; Li Q; Li F
Abdom Radiol (NY); 2022 Jan; 47(1):85-93. PubMed ID: 34705087
[TBL] [Abstract][Full Text] [Related]
5. [Performance of the Combined Model Based on Both Clinicopathological and CT Texture Features in Predicting Liver Metastasis of High-risk Gastrointestinal Stromal Tumors].
Zheng J; Wang X; Xia Y; Jiang HT
Zhongguo Yi Xue Ke Xue Yuan Xue Bao; 2022 Feb; 44(1):53-59. PubMed ID: 35300765
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Radiomics analysis of contrast-enhanced computerized tomography for differentiation of gastric schwannomas from gastric gastrointestinal stromal tumors.
Zhang C; Wang C; Mao G; Cheng G; Ji H; He L; Yang Y; Hu H; Wang J
J Cancer Res Clin Oncol; 2024 Feb; 150(2):87. PubMed ID: 38336926
[TBL] [Abstract][Full Text] [Related]
8. Prediction of Ki-67 expression in gastrointestinal stromal tumors using radiomics of plain and multiphase contrast-enhanced CT.
Liu Y; He C; Fang W; Peng L; Shi F; Xia Y; Zhou Q; Zhang R; Li C
Eur Radiol; 2023 Nov; 33(11):7609-7617. PubMed ID: 37266658
[TBL] [Abstract][Full Text] [Related]
9. Application Values of 2D and 3D Radiomics Models Based on CT Plain Scan in Differentiating Benign from Malignant Ovarian Tumors.
Li S; Liu J; Xiong Y; Han Y; Pang P; Luo P; Fan B
Biomed Res Int; 2022; 2022():5952296. PubMed ID: 35224097
[TBL] [Abstract][Full Text] [Related]
10. Value of contrast-enhanced CT based radiomic machine learning algorithm in differentiating gastrointestinal stromal tumors with KIT exon 11 mutation: a two-center study.
Liu B; Liu H; Zhang L; Song Y; Yang S; Zheng Z; Zhao J; Hou F; Zhang J
Diagn Interv Radiol; 2022 Jan; 28(1):29-38. PubMed ID: 35142612
[TBL] [Abstract][Full Text] [Related]
11. Radiomics signatures based on contrast-enhanced CT for preoperative prediction of the Ki-67 proliferation state in gastrointestinal stromal tumors.
Liu M; Bian J
Jpn J Radiol; 2023 Jul; 41(7):741-751. PubMed ID: 36652141
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Prediction of high Ki-67 proliferation index of gastrointestinal stromal tumors based on CT at non-contrast-enhanced and different contrast-enhanced phases.
Xie Z; Suo S; Zhang W; Zhang Q; Dai Y; Song Y; Li X; Zhou Y
Eur Radiol; 2024 Apr; 34(4):2223-2232. PubMed ID: 37773213
[TBL] [Abstract][Full Text] [Related]
14. A contrast-enhanced CT-based whole-spleen radiomics signature for early prediction of oxaliplatin-related thrombocytopenia in patients with gastrointestinal malignancies: a retrospective study.
Dai Y; Cheng Y; Zhou Z; Li Z; Luo Y; Qiu H
PeerJ; 2023; 11():e16230. PubMed ID: 37849829
[TBL] [Abstract][Full Text] [Related]
15. Value of MRI Radiomics Based on Enhanced T1WI Images in Prediction of Meningiomas Grade.
Chu H; Lin X; He J; Pang P; Fan B; Lei P; Guo D; Ye C
Acad Radiol; 2021 May; 28(5):687-693. PubMed ID: 32418785
[TBL] [Abstract][Full Text] [Related]
16. A radiomics approach for automated diagnosis of ovarian neoplasm malignancy in computed tomography.
Li S; Liu J; Xiong Y; Pang P; Lei P; Zou H; Zhang M; Fan B; Luo P
Sci Rep; 2021 Apr; 11(1):8730. PubMed ID: 33888749
[TBL] [Abstract][Full Text] [Related]
17. Prediction of recurrence-free survival and adjuvant therapy benefit in patients with gastrointestinal stromal tumors based on radiomics features.
Wang FH; Zheng HL; Li JT; Li P; Zheng CH; Chen QY; Huang CM; Xie JW
Radiol Med; 2022 Oct; 127(10):1085-1097. PubMed ID: 36057930
[TBL] [Abstract][Full Text] [Related]
18. Risk stratification for 1- to 2-cm gastric gastrointestinal stromal tumors: visual assessment of CT and EUS high-risk features versus CT radiomics analysis.
Jia X; Wan L; Chen X; Ji W; Huang S; Qi Y; Cui J; Wei S; Cheng J; Chai F; Feng C; Liu Y; Zhang H; Sun Y; Hong N; Rao S; Zhang X; Xiao Y; Ye Y; Tang L; Wang Y
Eur Radiol; 2023 Apr; 33(4):2768-2778. PubMed ID: 36449061
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Computer-aided diagnosis of gastrointestinal stromal tumors: a radiomics method on endoscopic ultrasound image.
Li X; Jiang F; Guo Y; Jin Z; Wang Y
Int J Comput Assist Radiol Surg; 2019 Oct; 14(10):1635-1645. PubMed ID: 31049803
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]