141 related articles for article (PubMed ID: 38127096)
21. 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]
22. Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning.
Lin YC; Lin G; Pandey S; Yeh CH; Wang JJ; Lin CY; Ho TY; Ko SF; Ng SH
Eur Radiol; 2023 Sep; 33(9):6548-6556. PubMed ID: 37338554
[TBL] [Abstract][Full Text] [Related]
23. External validation of a CT-based radiomics signature in oropharyngeal cancer: Assessing sources of variation.
Guevorguian P; Chinnery T; Lang P; Nichols A; Mattonen SA
Radiother Oncol; 2023 Jan; 178():109434. PubMed ID: 36464179
[TBL] [Abstract][Full Text] [Related]
24. Development and Validation of Noninvasive MRI-Based Signature for Preoperative Prediction of Early Recurrence in Perihilar Cholangiocarcinoma.
Zhao J; Zhang W; Zhu YY; Zheng HY; Xu L; Zhang J; Liu SY; Li FY; Song B
J Magn Reson Imaging; 2022 Mar; 55(3):787-802. PubMed ID: 34296802
[TBL] [Abstract][Full Text] [Related]
25. Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics.
Liu J; Wu Y; Jia W; Han M; Chen Y; Li J; Wu B; Yin S; Zhang X; Chen J; Yu P; Luo H; Tu J; Zhou F; Cheng X; Yi Y
Front Neurosci; 2023; 17():1110579. PubMed ID: 37214402
[TBL] [Abstract][Full Text] [Related]
26. Machine Learning Classifier for Preoperative Prediction of Early Recurrence After Bronchial Arterial Chemoembolization Treatment in Lung Cancer Patients.
Kong C; Lai L; Jin X; Chen W; Ding J; Zheng L; Zhang D; Ying X; Chen X; Chen M; Tu J; Ji J
Acad Radiol; 2023 Dec; 30(12):2880-2893. PubMed ID: 37225529
[TBL] [Abstract][Full Text] [Related]
27. Delta-volume radiomics of induction chemotherapy to predict outcome of subsequent chemoradiotherapy for locally advanced hypopharyngeal cancer.
Su CW; Lee JC; Chang YF; Su NW; Lee PH; Dai KY; Tai HC; Leu YS; Chen YJ
Tumori; 2022 Oct; 108(5):450-460. PubMed ID: 34423708
[TBL] [Abstract][Full Text] [Related]
28. Framework for Machine Learning of CT and PET Radiomics to Predict Local Failure after Radiotherapy in Locally Advanced Head and Neck Cancers.
Devakumar D; Sunny G; Sasidharan BK; Bowen SR; Nadaraj A; Jeyseelan L; Mathew M; Irodi A; Isiah R; Pavamani S; John S; T Thomas HM
J Med Phys; 2021; 46(3):181-188. PubMed ID: 34703102
[TBL] [Abstract][Full Text] [Related]
29. Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer.
Xiong S; Dong W; Deng Z; Jiang M; Li S; Hu B; Liu X; Chen L; Xu S; Fan B; Fu B
Cancer Med; 2023 Aug; 12(15):15868-15880. PubMed ID: 37434436
[TBL] [Abstract][Full Text] [Related]
30. Development and validation of a
Liu H; Cui Y; Chang C; Zhou Z; Zhang Y; Ma C; Yin Y; Wang R
BMC Cancer; 2024 Jan; 24(1):150. PubMed ID: 38291351
[TBL] [Abstract][Full Text] [Related]
31. A prediction model for degree of differentiation for resectable locally advanced esophageal squamous cell carcinoma based on CT images using radiomics and machine-learning.
Kawahara D; Murakami Y; Tani S; Nagata Y
Br J Radiol; 2021 Aug; 94(1124):20210525. PubMed ID: 34235955
[TBL] [Abstract][Full Text] [Related]
32. 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]
33. Simple delineations cannot substitute full 3d tumor delineations for MR-based radiomics prediction of locoregional control in oropharyngeal cancer.
Bos P; van den Brekel MWM; Taghavi M; Gouw ZAR; Al-Mamgani A; Waktola S; Aerts HJWL; Beets-Tan RGH; Castelijns JA; Jasperse B
Eur J Radiol; 2022 Mar; 148():110167. PubMed ID: 35086005
[TBL] [Abstract][Full Text] [Related]
34. A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features.
Tan Y; Feng LJ; Huang YH; Xue JW; Long LL; Feng ZB
Transl Oncol; 2024 Feb; 40():101864. PubMed ID: 38141376
[TBL] [Abstract][Full Text] [Related]
35. Investigation of radiomic signatures for local recurrence using primary tumor texture analysis in oropharyngeal head and neck cancer patients.
M. D. Anderson Cancer Center Head and Neck Quantitative Imaging Working Group
Sci Rep; 2018 Jan; 8(1):1524. PubMed ID: 29367653
[TBL] [Abstract][Full Text] [Related]
36. 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]
37. Radiomic and clinical data integration using machine learning predict the efficacy of anti-PD-1 antibodies-based combinational treatment in advanced breast cancer: a multicentered study.
Zhao J; Sun Z; Yu Y; Yuan Z; Lin Y; Tan Y; Duan X; Yao H; Wang Y; Liu J
J Immunother Cancer; 2023 May; 11(5):. PubMed ID: 37217246
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. 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]
40. Contrast-enhanced CT radiomics features to predict recurrence of locally advanced oesophageal squamous cell cancer within 2 years after trimodal therapy: A case-control study.
Tang S; Ou J; Wu YP; Li R; Chen TW; Zhang XM
Medicine (Baltimore); 2021 Jul; 100(27):e26557. PubMed ID: 34232198
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
