370 related articles for article (PubMed ID: 33882244)
1. Current progress and quality of radiomic studies for predicting EGFR mutation in patients with non-small cell lung cancer using PET/CT images: a systematic review.
Abdurixiti M; Nijiati M; Shen R; Ya Q; Abuduxiku N; Nijiati M
Br J Radiol; 2021 Jun; 94(1122):20201272. PubMed ID: 33882244
[TBL] [Abstract][Full Text] [Related]
2. Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.
Shiri I; Maleki H; Hajianfar G; Abdollahi H; Ashrafinia S; Hatt M; Zaidi H; Oveisi M; Rahmim A
Mol Imaging Biol; 2020 Aug; 22(4):1132-1148. PubMed ID: 32185618
[TBL] [Abstract][Full Text] [Related]
3. Value of pre-therapy
Zhang J; Zhao X; Zhao Y; Zhang J; Zhang Z; Wang J; Wang Y; Dai M; Han J
Eur J Nucl Med Mol Imaging; 2020 May; 47(5):1137-1146. PubMed ID: 31728587
[TBL] [Abstract][Full Text] [Related]
4. Systematic Review, Meta-Analysis and Radiomics Quality Score Assessment of CT Radiomics-Based Models Predicting Tumor EGFR Mutation Status in Patients with Non-Small-Cell Lung Cancer.
Felfli M; Liu Y; Zerka F; Voyton C; Thinnes A; Jacques S; Iannessi A; Bodard S
Int J Mol Sci; 2023 Jul; 24(14):. PubMed ID: 37511192
[TBL] [Abstract][Full Text] [Related]
5. Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images.
Shiri I; Amini M; Nazari M; Hajianfar G; Haddadi Avval A; Abdollahi H; Oveisi M; Arabi H; Rahmim A; Zaidi H
Comput Biol Med; 2022 Mar; 142():105230. PubMed ID: 35051856
[TBL] [Abstract][Full Text] [Related]
6. IMPORTANCE of PRETREATMENT 18F-FDG PET/CT TEXTURE ANALYSIS in PREDICTING EGFR and ALK MUTATION in PATIENTS with NON-SMALL CELL LUNG CANCER.
Agüloğlu N; Aksu A; Akyol M; Katgı N; Doksöz TÇ
Nuklearmedizin; 2022 Dec; 61(6):433-439. PubMed ID: 35977671
[TBL] [Abstract][Full Text] [Related]
7. The diagnostic and predictive efficacy of
Guo Y; Zhu H; Yao Z; Liu F; Yang D
Eur J Radiol; 2021 Aug; 141():109792. PubMed ID: 34062472
[TBL] [Abstract][Full Text] [Related]
8. Assessing EGFR gene mutation status in non-small cell lung cancer with imaging features from PET/CT.
Jiang M; Zhang Y; Xu J; Ji M; Guo Y; Guo Y; Xiao J; Yao X; Shi H; Zeng M
Nucl Med Commun; 2019 Aug; 40(8):842-849. PubMed ID: 31290849
[TBL] [Abstract][Full Text] [Related]
9. Usefulness of gradient tree boosting for predicting histological subtype and EGFR mutation status of non-small cell lung cancer on
Koyasu S; Nishio M; Isoda H; Nakamoto Y; Togashi K
Ann Nucl Med; 2020 Jan; 34(1):49-57. PubMed ID: 31659591
[TBL] [Abstract][Full Text] [Related]
10. Using contrast-enhanced CT and non-contrast-enhanced CT to predict EGFR mutation status in NSCLC patients-a radiomics nomogram analysis.
Yang X; Liu M; Ren Y; Chen H; Yu P; Wang S; Zhang R; Dai H; Wang C
Eur Radiol; 2022 Apr; 32(4):2693-2703. PubMed ID: 34807270
[TBL] [Abstract][Full Text] [Related]
11. Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.
Nair JKR; Saeed UA; McDougall CC; Sabri A; Kovacina B; Raidu BVS; Khokhar RA; Probst S; Hirsh V; Chankowsky J; Van Kempen LC; Taylor J
Can Assoc Radiol J; 2021 Feb; 72(1):109-119. PubMed ID: 32063026
[TBL] [Abstract][Full Text] [Related]
12. Radiomics for the prediction of EGFR mutation subtypes in non-small cell lung cancer.
Li S; Ding C; Zhang H; Song J; Wu L
Med Phys; 2019 Oct; 46(10):4545-4552. PubMed ID: 31376283
[TBL] [Abstract][Full Text] [Related]
13. Radiomics signature: A potential and incremental predictor for EGFR mutation status in NSCLC patients, comparison with CT morphology.
Tu W; Sun G; Fan L; Wang Y; Xia Y; Guan Y; Li Q; Zhang D; Liu S; Li Z
Lung Cancer; 2019 Jun; 132():28-35. PubMed ID: 31097090
[TBL] [Abstract][Full Text] [Related]
14. Impact of experimental design on PET radiomics in predicting somatic mutation status.
Yip SSF; Parmar C; Kim J; Huynh E; Mak RH; Aerts HJWL
Eur J Radiol; 2017 Dec; 97():8-15. PubMed ID: 29153372
[TBL] [Abstract][Full Text] [Related]
15. Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives.
Chetan MR; Gleeson FV
Eur Radiol; 2021 Feb; 31(2):1049-1058. PubMed ID: 32809167
[TBL] [Abstract][Full Text] [Related]
16. A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma.
Chang C; Zhou S; Yu H; Zhao W; Ge Y; Duan S; Wang R; Qian X; Lei B; Wang L; Liu L; Ruan M; Yan H; Sun X; Xie W
Eur Radiol; 2021 Aug; 31(8):6259-6268. PubMed ID: 33544167
[TBL] [Abstract][Full Text] [Related]
17. Radiomic Detection of EGFR Mutations in NSCLC.
Rossi G; Barabino E; Fedeli A; Ficarra G; Coco S; Russo A; Adamo V; Buemi F; Zullo L; Dono M; De Luca G; Longo L; Dal Bello MG; Tagliamento M; Alama A; Cittadini G; Pronzato P; Genova C
Cancer Res; 2021 Feb; 81(3):724-731. PubMed ID: 33148663
[TBL] [Abstract][Full Text] [Related]
18. Hybrid deep multi-task learning radiomics approach for predicting EGFR mutation status of non-small cell lung cancer in CT images.
Gong J; Fu F; Ma X; Wang T; Ma X; You C; Zhang Y; Peng W; Chen H; Gu Y
Phys Med Biol; 2023 Dec; 68(24):. PubMed ID: 37972417
[No Abstract] [Full Text] [Related]
19. Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis.
Nguyen HS; Ho DKN; Nguyen NN; Tran HM; Tam KW; Le NQK
Acad Radiol; 2024 Feb; 31(2):660-683. PubMed ID: 37120403
[TBL] [Abstract][Full Text] [Related]
20. CT-based non-invasive identification of the most common gene mutation status in patients with non-small cell lung cancer.
Chen Z; Gao S; Ding C; Luo T; Xu J; Xu S; Li S
Med Phys; 2024 Mar; 51(3):1872-1882. PubMed ID: 37706584
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
