351 related articles for article (PubMed ID: 36131163)
21. Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging.
Dai H; Lu M; Huang B; Tang M; Pang T; Liao B; Cai H; Huang M; Zhou Y; Chen X; Ding H; Feng ST
Quant Imaging Med Surg; 2021 May; 11(5):1836-1853. PubMed ID: 33936969
[TBL] [Abstract][Full Text] [Related]
22. Preoperative Evaluation of Gd-EOB-DTPA-Enhanced MRI Radiomics-Based Nomogram in Small Solitary Hepatocellular Carcinoma (≤3 cm) With Microvascular Invasion: A Two-Center Study.
Tian Y; Hua H; Peng Q; Zhang Z; Wang X; Han J; Ma W; Chen J
J Magn Reson Imaging; 2022 Nov; 56(5):1459-1472. PubMed ID: 35298849
[TBL] [Abstract][Full Text] [Related]
23. Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy.
Zhao Y; Wu J; Zhang Q; Hua Z; Qi W; Wang N; Lin T; Sheng L; Cui D; Liu J; Song Q; Li X; Wu T; Guo Y; Cui J; Liu A
J Magn Reson Imaging; 2021 Apr; 53(4):1066-1079. PubMed ID: 33217114
[TBL] [Abstract][Full Text] [Related]
24. Radiomics nomogram for prediction of glypican-3 positive hepatocellular carcinoma based on hepatobiliary phase imaging.
Zhang N; Wu M; Zhou Y; Yu C; Shi D; Wang C; Gao M; Lv Y; Zhu S
Front Oncol; 2023; 13():1209814. PubMed ID: 37841420
[TBL] [Abstract][Full Text] [Related]
25. Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study.
Jin P; Shen J; Yang L; Zhang J; Shen A; Bao J; Wang X
BMC Med Imaging; 2023 Mar; 23(1):47. PubMed ID: 36991347
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.
Sim Y; Kim M; Kim J; Lee SK; Han K; Sohn B
Eur Radiol; 2024 May; 34(5):3102-3112. PubMed ID: 37848774
[TBL] [Abstract][Full Text] [Related]
28. Gadoxetic Acid-Enhanced MRI-Based Radiomics Signature: A Potential Imaging Biomarker for Identifying Cytokeratin 19-Positive Hepatocellular Carcinoma.
Hu X; Wang Q; Huang G; He X; Sparrelid E; Brismar TB; Fan Y
Comput Math Methods Med; 2023; 2023():5424204. PubMed ID: 36814805
[TBL] [Abstract][Full Text] [Related]
29. A predictive model integrating deep and radiomics features based on gadobenate dimeglumine-enhanced MRI for postoperative early recurrence of hepatocellular carcinoma.
Gao W; Wang W; Song D; Yang C; Zhu K; Zeng M; Rao SX; Wang M
Radiol Med; 2022 Mar; 127(3):259-271. PubMed ID: 35129757
[TBL] [Abstract][Full Text] [Related]
30. Association between relative liver enhancement on gadoxetic acid enhanced magnetic resonance images and histologic grade of hepatocellular carcinoma.
Jin YJ; Cho SG; Lee KY; Kim JM; Lee JW
Medicine (Baltimore); 2017 Jul; 96(30):e7580. PubMed ID: 28746206
[TBL] [Abstract][Full Text] [Related]
31. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
[TBL] [Abstract][Full Text] [Related]
32. A clinical-radiomic-pathomic model for prognosis prediction in patients with hepatocellular carcinoma after radical resection.
Xie Q; Zhao Z; Yang Y; Wang X; Wu W; Jiang H; Hao W; Peng R; Luo C
Cancer Med; 2024 Jun; 13(11):e7374. PubMed ID: 38864473
[TBL] [Abstract][Full Text] [Related]
33. Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature.
Wu M; Tan H; Gao F; Hai J; Ning P; Chen J; Zhu S; Wang M; Dou S; Shi D
Eur Radiol; 2019 Jun; 29(6):2802-2811. PubMed ID: 30406313
[TBL] [Abstract][Full Text] [Related]
34. Radiologic-Pathologic Correlation of Hepatobiliary Phase Hypointense Nodules without Arterial Phase Hyperenhancement at Gadoxetic Acid-enhanced MRI: A Multicenter Study.
Joo I; Kim SY; Kang TW; Kim YK; Park BJ; Lee YJ; Choi JI; Lee CH; Park HS; Lee K; Kim H; Yu E; Kang HJ; Ha SY; Kim JY; Ahn S; Jung ES; Kim BH; Han HS; Lee JM
Radiology; 2020 Aug; 296(2):335-345. PubMed ID: 32484414
[TBL] [Abstract][Full Text] [Related]
35. Preoperative Diagnosis of Dual-Phenotype Hepatocellular Carcinoma Using Enhanced MRI Radiomics Models.
Wu Q; Yu YX; Zhang T; Zhu WJ; Fan YF; Wang XM; Hu CH
J Magn Reson Imaging; 2023 Apr; 57(4):1185-1196. PubMed ID: 36190656
[TBL] [Abstract][Full Text] [Related]
36. Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging.
Chen S; Feng S; Wei J; Liu F; Li B; Li X; Hou Y; Gu D; Tang M; Xiao H; Jia Y; Peng S; Tian J; Kuang M
Eur Radiol; 2019 Aug; 29(8):4177-4187. PubMed ID: 30666445
[TBL] [Abstract][Full Text] [Related]
37. Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks.
Said D; Carbonell G; Stocker D; Hectors S; Vietti-Violi N; Bane O; Chin X; Schwartz M; Tabrizian P; Lewis S; Greenspan H; Jégou S; Schiratti JB; Jehanno P; Taouli B
Eur Radiol; 2023 Sep; 33(9):6020-6032. PubMed ID: 37071167
[TBL] [Abstract][Full Text] [Related]
38. [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]
39. 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]
40. Added value of CE-CT radiomics to predict high Ki-67 expression in hepatocellular carcinoma.
Zhao YM; Xie SS; Wang J; Zhang YM; Li WC; Ye ZX; Shen W
BMC Med Imaging; 2023 Sep; 23(1):138. PubMed ID: 37737166
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]