184 related articles for article (PubMed ID: 34264747)
1. Machine Learning Radiomics Model for Early Identification of Small-Cell Lung Cancer on Computed Tomography Scans.
Shah RP; Selby HM; Mukherjee P; Verma S; Xie P; Xu Q; Das M; Malik S; Gevaert O; Napel S
JCO Clin Cancer Inform; 2021 Jun; 5():746-757. PubMed ID: 34264747
[TBL] [Abstract][Full Text] [Related]
2. Radiomics for Classification of Lung Cancer Histological Subtypes Based on Nonenhanced Computed Tomography.
E L; Lu L; Li L; Yang H; Schwartz LH; Zhao B
Acad Radiol; 2019 Sep; 26(9):1245-1252. PubMed ID: 30502076
[TBL] [Abstract][Full Text] [Related]
3. Radiomic analysis for early differentiation of lung cancer recurrence from fibrosis in patients treated with lung stereotactic ablative radiotherapy.
Kunkyab T; Mou B; Jirasek A; Haston C; Andrews J; Thomas S; Hyde D
Phys Med Biol; 2023 Aug; 68(16):. PubMed ID: 37164024
[No Abstract] [Full Text] [Related]
4. Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans.
Khorrami M; Bera K; Thawani R; Rajiah P; Gupta A; Fu P; Linden P; Pennell N; Jacono F; Gilkeson RC; Velcheti V; Madabhushi A
Eur J Cancer; 2021 May; 148():146-158. PubMed ID: 33743483
[TBL] [Abstract][Full Text] [Related]
5. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
[TBL] [Abstract][Full Text] [Related]
6. Histologic subtype classification of non-small cell lung cancer using PET/CT images.
Han Y; Ma Y; Wu Z; Zhang F; Zheng D; Liu X; Tao L; Liang Z; Yang Z; Li X; Huang J; Guo X
Eur J Nucl Med Mol Imaging; 2021 Feb; 48(2):350-360. PubMed ID: 32776232
[TBL] [Abstract][Full Text] [Related]
7. The CT delta-radiomics based machine learning approach in evaluating multiple primary lung adenocarcinoma.
Ma Y; Li J; Xu X; Zhang Y; Lin Y
BMC Cancer; 2022 Sep; 22(1):949. PubMed ID: 36057553
[TBL] [Abstract][Full Text] [Related]
8. Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.
Hu J; Zhao Y; Li M; Liu Y; Wang F; Weng Q; You R; Cao D
Eur J Radiol; 2020 May; 126():108929. PubMed ID: 32169748
[TBL] [Abstract][Full Text] [Related]
9. Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients.
Nazari M; Shiri I; Zaidi H
Comput Biol Med; 2021 Feb; 129():104135. PubMed ID: 33254045
[TBL] [Abstract][Full Text] [Related]
10. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.
Jiang C; Luo Y; Yuan J; You S; Chen Z; Wu M; Wang G; Gong J
Eur Radiol; 2020 Jul; 30(7):4050-4057. PubMed ID: 32112116
[TBL] [Abstract][Full Text] [Related]
11. Use of radiomics based on
Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
[TBL] [Abstract][Full Text] [Related]
12. Differentiating Peripherally-Located Small Cell Lung Cancer From Non-small Cell Lung Cancer Using a CT Radiomic Approach.
Chen BT; Chen Z; Ye N; Mambetsariev I; Fricke J; Daniel E; Wang G; Wong CW; Rockne RC; Colen RR; Nasser MW; Batra SK; Holodny AI; Sampath S; Salgia R
Front Oncol; 2020; 10():593. PubMed ID: 32391274
[TBL] [Abstract][Full Text] [Related]
13. Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma.
Xu F; Zhu W; Shen Y; Wang J; Xu R; Qutesh C; Song L; Gan Y; Pu C; Hu H
Front Oncol; 2020; 10():872. PubMed ID: 32850301
[No Abstract] [Full Text] [Related]
14. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
[TBL] [Abstract][Full Text] [Related]
15. Machine learning based on clinico-biological features integrated
Ren C; Zhang J; Qi M; Zhang J; Zhang Y; Song S; Sun Y; Cheng J
Eur J Nucl Med Mol Imaging; 2021 May; 48(5):1538-1549. PubMed ID: 33057772
[TBL] [Abstract][Full Text] [Related]
16. Machine learning-based texture analysis for differentiation of radiologically indeterminate small adrenal tumors on adrenal protocol CT scans.
Moawad AW; Ahmed A; Fuentes DT; Hazle JD; Habra MA; Elsayes KM
Abdom Radiol (NY); 2021 Oct; 46(10):4853-4863. PubMed ID: 34085089
[TBL] [Abstract][Full Text] [Related]
17. A Machine Learning Approach Using PET/CT-based Radiomics for Prediction of PD-L1 Expression in Non-small Cell Lung Cancer.
Lim CH; Koh YW; Hyun SH; Lee SJ
Anticancer Res; 2022 Dec; 42(12):5875-5884. PubMed ID: 36456151
[TBL] [Abstract][Full Text] [Related]
18. A triple-classification for the evaluation of lung nodules manifesting as pure ground-glass sign: a CT-based radiomic analysis.
Yu Z; Xu C; Zhang Y; Ji F
BMC Med Imaging; 2022 Jul; 22(1):133. PubMed ID: 35896975
[TBL] [Abstract][Full Text] [Related]
19. Evaluating Histological Subtypes Classification of Primary Lung Cancers on Unenhanced Computed Tomography Based on Random Forest Model.
Huang J; He W; Xu H; Yang S; Dai J; Guo W; Zeng M
J Healthc Eng; 2023; 2023():8964676. PubMed ID: 36794098
[TBL] [Abstract][Full Text] [Related]
20. Radiomics nomogram for preoperative differentiation of pulmonary mucinous adenocarcinoma from tuberculoma in solitary pulmonary solid nodules.
Zhang J; Hao L; Qi M; Xu Q; Zhang N; Feng H; Shi G
BMC Cancer; 2023 Mar; 23(1):261. PubMed ID: 36944978
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]