196 related articles for article (PubMed ID: 38515051)
1. Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma.
Ma Y; Gong Y; Qiu Q; Ma C; Yu S
BMC Cancer; 2024 Mar; 24(1):363. PubMed ID: 38515051
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. [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]
4. Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carcinoma and cholangiocarcinoma to inform optimal treatment planning?
Liu X; Khalvati F; Namdar K; Fischer S; Lewis S; Taouli B; Haider MA; Jhaveri KS
Eur Radiol; 2021 Jan; 31(1):244-255. PubMed ID: 32749585
[TBL] [Abstract][Full Text] [Related]
5. Development and Validation of Contrast-Enhanced CT-Based Deep Transfer Learning and Combined Clinical-Radiomics Model to Discriminate Thymomas and Thymic Cysts: A Multicenter Study.
Yang Y; Cheng J; Peng Z; Yi L; Lin Z; He A; Jin M; Cui C; Liu Y; Zhong Q; Zuo M
Acad Radiol; 2024 Apr; 31(4):1615-1628. PubMed ID: 37949702
[TBL] [Abstract][Full Text] [Related]
6. Five machine learning-based radiomics models for preoperative prediction of histological grade in hepatocellular carcinoma.
Wu C; Du X; Zhang Y; Zhu L; Chen J; Chen Y; Wei Y; Liu Y
J Cancer Res Clin Oncol; 2023 Nov; 149(16):15103-15112. PubMed ID: 37624395
[TBL] [Abstract][Full Text] [Related]
7. Preoperative prediction of macrotrabecular-massive hepatocellular carcinoma through dynamic contrast-enhanced magnetic resonance imaging-based radiomics.
Zhang Y; He D; Liu J; Wei YG; Shi LL
World J Gastroenterol; 2023 Apr; 29(13):2001-2014. PubMed ID: 37155523
[TBL] [Abstract][Full Text] [Related]
8. Computed tomography-based radiomics machine learning classifiers to differentiate type I and type II epithelial ovarian cancers.
Li J; Li X; Ma J; Wang F; Cui S; Ye Z
Eur Radiol; 2023 Jul; 33(7):5193-5204. PubMed ID: 36515713
[TBL] [Abstract][Full Text] [Related]
9. Application of machine learning-based multi-sequence MRI radiomics in diagnosing anterior cruciate ligament tears.
Cheng Q; Lin H; Zhao J; Lu X; Wang Q
J Orthop Surg Res; 2024 Jan; 19(1):99. PubMed ID: 38297322
[TBL] [Abstract][Full Text] [Related]
10. Machine learning for differentiation of lipid-poor adrenal adenoma and subclinical pheochromocytoma based on multiphase CT imaging radiomics.
Xiao DX; Zhong JP; Peng JD; Fan CG; Wang XC; Wen XL; Liao WW; Wang J; Yin XF
BMC Med Imaging; 2023 Oct; 23(1):159. PubMed ID: 37845636
[TBL] [Abstract][Full Text] [Related]
11. Hepatocellular carcinoma pathologic grade prediction using radiomics and machine learning models of gadoxetic acid-enhanced MRI: a two-center study.
Han YE; Cho Y; Kim MJ; Park BJ; Sung DJ; Han NY; Sim KC; Park YS; Park BN
Abdom Radiol (NY); 2023 Jan; 48(1):244-256. PubMed ID: 36131163
[TBL] [Abstract][Full Text] [Related]
12. CT radiomics based on different machine learning models for classifying gross tumor volume and normal liver tissue in hepatocellular carcinoma.
Zhang HW; Huang DL; Wang YR; Zhong HS; Pang HW
Cancer Imaging; 2024 Jan; 24(1):20. PubMed ID: 38279133
[TBL] [Abstract][Full Text] [Related]
13. Machine learning-based radiomics analysis of preoperative functional liver reserve with MRI and CT image.
Zhu L; Wang F; Chen X; Dong Q; Xia N; Chen J; Li Z; Zhu C
BMC Med Imaging; 2023 Jul; 23(1):94. PubMed ID: 37460944
[TBL] [Abstract][Full Text] [Related]
14. Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules.
Mokrane FZ; Lu L; Vavasseur A; Otal P; Peron JM; Luk L; Yang H; Ammari S; Saenger Y; Rousseau H; Zhao B; Schwartz LH; Dercle L
Eur Radiol; 2020 Jan; 30(1):558-570. PubMed ID: 31444598
[TBL] [Abstract][Full Text] [Related]
15. A machine-learning model based on dynamic contrast-enhanced MRI for preoperative differentiation between hepatocellular carcinoma and combined hepatocellular-cholangiocarcinoma.
Deng X; Liao Z
Clin Radiol; 2024 Jun; 79(6):e817-e825. PubMed ID: 38413354
[TBL] [Abstract][Full Text] [Related]
16. Comparison of Conventional Gadoxetate Disodium-Enhanced MRI Features and Radiomics Signatures With Machine Learning for Diagnosing Microvascular Invasion.
Chen Y; Xia Y; Tolat PP; Long L; Jiang Z; Huang Z; Tang Q
AJR Am J Roentgenol; 2021 Jun; 216(6):1510-1520. PubMed ID: 33826360
[No Abstract] [Full Text] [Related]
17. Distinguishing intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma by computed tomography and magnetic resonance imaging using the Bayesian method: a bi-center study.
Ichikawa S; Isoda H; Shimizu T; Tamada D; Taura K; Togashi K; Onishi H; Motosugi U
Eur Radiol; 2020 Nov; 30(11):5992-6002. PubMed ID: 32500195
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Multi-phase contrast-enhanced magnetic resonance image-based radiomics-combined machine learning reveals microscopic ultra-early hepatocellular carcinoma lesions.
Sun K; Shi L; Qiu J; Pan Y; Wang X; Wang H
Eur J Nucl Med Mol Imaging; 2022 Jul; 49(8):2917-2928. PubMed ID: 35230493
[TBL] [Abstract][Full Text] [Related]
20. Radiomics-based distinction of small (≤2 cm) hepatocellular carcinoma and precancerous lesions based on unenhanced MRI.
Gao X; Bian J; Luo J; Guo K; Xiang Y; Liu H; Ding J
Clin Radiol; 2024 May; 79(5):e659-e664. PubMed ID: 38341345
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]