522 related articles for article (PubMed ID: 34862094)
1. Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma.
Yang Y; Zhou Y; Zhou C; Ma X
Eur J Surg Oncol; 2022 May; 48(5):1068-1077. PubMed ID: 34862094
[TBL] [Abstract][Full Text] [Related]
2. Using deep learning to predict microvascular invasion in hepatocellular carcinoma based on dynamic contrast-enhanced MRI combined with clinical parameters.
Song D; Wang Y; Wang W; Wang Y; Cai J; Zhu K; Lv M; Gao Q; Zhou J; Fan J; Rao S; Wang M; Wang X
J Cancer Res Clin Oncol; 2021 Dec; 147(12):3757-3767. PubMed ID: 33839938
[TBL] [Abstract][Full Text] [Related]
3. A novel multimodal deep learning model for preoperative prediction of microvascular invasion and outcome in hepatocellular carcinoma.
Wang F; Chen Q; Chen Y; Zhu Y; Zhang Y; Cao D; Zhou W; Liang X; Yang Y; Lin L; Hu H
Eur J Surg Oncol; 2023 Jan; 49(1):156-164. PubMed ID: 36333180
[TBL] [Abstract][Full Text] [Related]
4. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma.
Xu X; Zhang HL; Liu QP; Sun SW; Zhang J; Zhu FP; Yang G; Yan X; Zhang YD; Liu XS
J Hepatol; 2019 Jun; 70(6):1133-1144. PubMed ID: 30876945
[TBL] [Abstract][Full Text] [Related]
5. Prediction of preoperative microvascular invasion by dynamic radiomic analysis based on contrast-enhanced computed tomography.
Zhou Z; Xia T; Zhang T; Du M; Zhong J; Huang Y; Xuan K; Xu G; Wan Z; Ju S; Xu J
Abdom Radiol (NY); 2024 Feb; 49(2):611-624. PubMed ID: 38051358
[TBL] [Abstract][Full Text] [Related]
6. Influence of different region of interest sizes on CT-based radiomics model for microvascular invasion prediction in hepatocellular carcinoma.
Zhao H; Feng Z; Li H; Yao S; Zheng W; Rong P
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2022 Aug; 47(8):1049-1057. PubMed ID: 36097772
[TBL] [Abstract][Full Text] [Related]
7. [Value of the application of enhanced CT radiomics and machine learning in preoperative prediction of microvascular invasion in hepatocellular carcinoma].
Yu YX; Hu CH; Wang XM; Fan YF; Hu MJ; Shi C; Hu S; Zhu M; Zhang Y
Zhonghua Yi Xue Za Zhi; 2021 May; 101(17):1239-1245. PubMed ID: 34865392
[No Abstract] [Full Text] [Related]
8. Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.
Jiang YQ; Cao SE; Cao S; Chen JN; Wang GY; Shi WQ; Deng YN; Cheng N; Ma K; Zeng KN; Yan XJ; Yang HZ; Huan WJ; Tang WM; Zheng Y; Shao CK; Wang J; Yang Y; Chen GH
J Cancer Res Clin Oncol; 2021 Mar; 147(3):821-833. PubMed ID: 32852634
[TBL] [Abstract][Full Text] [Related]
9. Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma.
Sun BY; Gu PY; Guan RY; Zhou C; Lu JW; Yang ZF; Pan C; Zhou PY; Zhu YP; Li JR; Wang ZT; Gao SS; Gan W; Yi Y; Luo Y; Qiu SJ
World J Surg Oncol; 2022 Jun; 20(1):189. PubMed ID: 35676669
[TBL] [Abstract][Full Text] [Related]
10. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT.
Ma X; Wei J; Gu D; Zhu Y; Feng B; Liang M; Wang S; Zhao X; Tian J
Eur Radiol; 2019 Jul; 29(7):3595-3605. PubMed ID: 30770969
[TBL] [Abstract][Full Text] [Related]
11. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma.
Chen YD; Zhang L; Zhou ZP; Lin B; Jiang ZJ; Tang C; Dang YW; Xia YW; Song B; Long LL
World J Gastroenterol; 2022 Aug; 28(31):4399-4416. PubMed ID: 36159011
[TBL] [Abstract][Full Text] [Related]
12. Radiomics analysis of [
Li Y; Zhang Y; Fang Q; Zhang X; Hou P; Wu H; Wang X
Eur J Nucl Med Mol Imaging; 2021 Jul; 48(8):2599-2614. PubMed ID: 33416951
[TBL] [Abstract][Full Text] [Related]
13. Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.
Yan M; Zhang X; Zhang B; Geng Z; Xie C; Yang W; Zhang S; Qi Z; Lin T; Ke Q; Li X; Wang S; Quan X
Eur Radiol; 2023 Jul; 33(7):4949-4961. PubMed ID: 36786905
[TBL] [Abstract][Full Text] [Related]
14. Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma.
Deng PZ; Zhao BG; Huang XH; Xu TF; Chen ZJ; Wei QF; Liu XY; Guo YQ; Yuan SG; Liao WJ
World J Gastroenterol; 2022 Aug; 28(31):4376-4389. PubMed ID: 36159012
[TBL] [Abstract][Full Text] [Related]
15. Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma based on kupffer phase radiomics features of sonazoid contrast-enhanced ultrasound (SCEUS): A prospective study.
Dong Y; Zuo D; Qiu YJ; Cao JY; Wang HZ; Yu LY; Wang WP
Clin Hemorheol Microcirc; 2022; 81(1):97-107. PubMed ID: 35001883
[TBL] [Abstract][Full Text] [Related]
16. A radiomics nomogram for the prediction of overall survival in patients with hepatocellular carcinoma after hepatectomy.
Liu Q; Li J; Liu F; Yang W; Ding J; Chen W; Wei Y; Li B; Zheng L
Cancer Imaging; 2020 Nov; 20(1):82. PubMed ID: 33198809
[TBL] [Abstract][Full Text] [Related]
17. Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutional study.
Ji GW; Zhu FP; Xu Q; Wang K; Wu MY; Tang WW; Li XC; Wang XH
EBioMedicine; 2019 Dec; 50():156-165. PubMed ID: 31735556
[TBL] [Abstract][Full Text] [Related]
18. Performances and variability of CT radiomics for the prediction of microvascular invasion and survival in patients with HCC: a matter of chance or standardisation?
Cannella R; Santinha J; Bèaufrere A; Ronot M; Sartoris R; Cauchy F; Bouattour M; Matos C; Papanikolaou N; Vilgrain V; Dioguardi Burgio M
Eur Radiol; 2023 Nov; 33(11):7618-7628. PubMed ID: 37338558
[TBL] [Abstract][Full Text] [Related]
19. Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.
Park S; Kim JH; Kim J; Joseph W; Lee D; Park SJ
Acta Radiol; 2023 Mar; 64(3):907-917. PubMed ID: 35570797
[TBL] [Abstract][Full Text] [Related]
20. Computed tomography-based deep-learning prediction of induction chemotherapy treatment response in locally advanced nasopharyngeal carcinoma.
Yang Y; Wang M; Qiu K; Wang Y; Ma X
Strahlenther Onkol; 2022 Feb; 198(2):183-193. PubMed ID: 34817635
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
