191 related articles for article (PubMed ID: 38279133)
1. 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]
2. 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]
3. 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]
4. Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.
Wan Q; Zhou J; Xia X; Hu J; Wang P; Peng Y; Zhang T; Sun J; Song Y; Yang G; Li X
Front Oncol; 2021; 11():683587. PubMed ID: 34868905
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. [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]
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. Non-Contrasted CT Radiomics for SAH Prognosis Prediction.
Shan D; Wang J; Qi P; Lu J; Wang D
Bioengineering (Basel); 2023 Aug; 10(8):. PubMed ID: 37627852
[TBL] [Abstract][Full Text] [Related]
9. A machine learning radiomics model based on bpMRI to predict bone metastasis in newly diagnosed prostate cancer patients.
Xinyang S; Shuang Z; Tianci S; Xiangyu H; Yangyang W; Mengying D; Jingran Z; Feng Y
Magn Reson Imaging; 2024 Apr; 107():15-23. PubMed ID: 38181835
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics.
Mao B; Ma J; Duan S; Xia Y; Tao Y; Zhang L
Eur Radiol; 2021 Jul; 31(7):4576-4586. PubMed ID: 33447862
[TBL] [Abstract][Full Text] [Related]
12. Prediction of Changes in Tumor Regression during Radiotherapy for Nasopharyngeal Carcinoma by Using the Computed Tomography-Based Radiomics.
Yang Y; Wu J; Mai W; Li H
Contrast Media Mol Imaging; 2022; 2022():3417480. PubMed ID: 36226269
[TBL] [Abstract][Full Text] [Related]
13. Machine learning based on gadoxetic acid-enhanced MRI for differentiating atypical intrahepatic mass-forming cholangiocarcinoma from poorly differentiated hepatocellular carcinoma.
Chen X; Chen Y; Chen H; Zhu J; Huang R; Xie J; Zhang T; Xie A; Li Y
Abdom Radiol (NY); 2023 Aug; 48(8):2525-2536. PubMed ID: 37169988
[TBL] [Abstract][Full Text] [Related]
14. Optimizing the radiomics-machine-learning model based on non-contrast enhanced CT for the simplified risk categorization of thymic epithelial tumors: A large cohort retrospective study.
Feng XL; Wang SZ; Chen HH; Huang YX; Xin YK; Zhang T; Cheng DL; Mao L; Li XL; Liu CX; Hu YC; Wang W; Cui GB; Nan HY
Lung Cancer; 2022 Apr; 166():150-160. PubMed ID: 35287067
[TBL] [Abstract][Full Text] [Related]
15. The CT-based intratumoral and peritumoral machine learning radiomics analysis in predicting lymph node metastasis in rectal carcinoma.
Yuan H; Xu X; Tu S; Chen B; Wei Y; Ma Y
BMC Gastroenterol; 2022 Nov; 22(1):463. PubMed ID: 36384504
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Predicting the risk stratification of gastrointestinal stromal tumors using machine learning-based ultrasound radiomics.
Zhuo M; Tang Y; Guo J; Qian Q; Xue E; Chen Z
J Med Ultrason (2001); 2024 Jan; 51(1):71-82. PubMed ID: 37798591
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
