405 related articles for article (PubMed ID: 35571081)
21. MRI-based radiomics analysis for predicting the EGFR mutation based on thoracic spinal metastases in lung adenocarcinoma patients.
Ren M; Yang H; Lai Q; Shi D; Liu G; Shuang X; Su J; Xie L; Dong Y; Jiang X
Med Phys; 2021 Sep; 48(9):5142-5151. PubMed ID: 34318502
[TBL] [Abstract][Full Text] [Related]
22. 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]
23. Enhancing brain metastasis prediction in non-small cell lung cancer: a deep learning-based segmentation and CT radiomics-based ensemble learning model.
Gong J; Wang T; Wang Z; Chu X; Hu T; Li M; Peng W; Feng F; Tong T; Gu Y
Cancer Imaging; 2024 Jan; 24(1):1. PubMed ID: 38167564
[TBL] [Abstract][Full Text] [Related]
24. Predicting EGFR mutation subtypes in lung adenocarcinoma using
Liu Q; Sun D; Li N; Kim J; Feng D; Huang G; Wang L; Song S
Transl Lung Cancer Res; 2020 Jun; 9(3):549-562. PubMed ID: 32676319
[TBL] [Abstract][Full Text] [Related]
25. CT Radiomics in Predicting EGFR Mutation in Non-small Cell Lung Cancer: A Single Institutional Study.
Wu S; Shen G; Mao J; Gao B
Front Oncol; 2020; 10():542957. PubMed ID: 33117680
[No Abstract] [Full Text] [Related]
26. Predicting PD-L1 expression status in patients with non-small cell lung cancer using [
Zhao X; Zhao Y; Zhang J; Zhang Z; Liu L; Zhao X
EJNMMI Res; 2023 Jan; 13(1):4. PubMed ID: 36682020
[TBL] [Abstract][Full Text] [Related]
27. Deep CNN Model Using CT Radiomics Feature Mapping Recognizes EGFR Gene Mutation Status of Lung Adenocarcinoma.
Zhang B; Qi S; Pan X; Li C; Yao Y; Qian W; Guan Y
Front Oncol; 2020; 10():598721. PubMed ID: 33643902
[TBL] [Abstract][Full Text] [Related]
28. Accuracy of machine learning in preoperative identification of genetic mutation status in lung cancer: A systematic review and meta-analysis.
Chen J; Chen A; Yang S; Liu J; Xie C; Jiang H
Radiother Oncol; 2024 Jul; 196():110325. PubMed ID: 38734145
[TBL] [Abstract][Full Text] [Related]
29. Establishing a predictive model for tumor mutation burden status based on CT radiomics and clinical features of non-small cell lung cancer patients.
Yang J; Shi W; Yang Z; Yu H; Wang M; Wei Y; Wen J; Zheng W; Zhang P; Zhao W; Chen L
Transl Lung Cancer Res; 2023 Apr; 12(4):808-823. PubMed ID: 37197623
[TBL] [Abstract][Full Text] [Related]
30. Predictive value of
Ma N; Yang W; Wang Q; Cui C; Hu Y; Wu Z
Front Oncol; 2024; 14():1281572. PubMed ID: 38361781
[TBL] [Abstract][Full Text] [Related]
31. Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.
Li S; Xie J; Liu J; Wu Y; Wang Z; Cao Z; Wen D; Zhang X; Wang B; Yang Y; Lu L; Dong X
J Comput Assist Tomogr; 2024 May-Jun 01; 48(3):498-507. PubMed ID: 38438336
[TBL] [Abstract][Full Text] [Related]
32. The predictive value of [
Gao J; Niu R; Shi Y; Shao X; Jiang Z; Ge X; Wang Y; Shao X
EJNMMI Res; 2023 Apr; 13(1):26. PubMed ID: 37014500
[TBL] [Abstract][Full Text] [Related]
33. Prediction of VEGF and EGFR Expression in Peripheral Lung Cancer Based on the Radiomics Model of Spectral CT Enhanced Images.
Wu L; Li J; Ruan X; Ren J; Ping X; Chen B
Int J Gen Med; 2022; 15():6725-6738. PubMed ID: 36039307
[TBL] [Abstract][Full Text] [Related]
34. 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]
35. 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]
36. Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.
Zhao W; Yang J; Ni B; Bi D; Sun Y; Xu M; Zhu X; Li C; Jin L; Gao P; Wang P; Hua Y; Li M
Cancer Med; 2019 Jul; 8(7):3532-3543. PubMed ID: 31074592
[TBL] [Abstract][Full Text] [Related]
37. Comparison of deep-learning and radiomics-based machine-learning methods for the identification of chronic obstructive pulmonary disease on low-dose computed tomography images.
Guan Y; Zhang D; Zhou X; Xia Y; Lu Y; Zheng X; He C; Liu S; Fan L
Quant Imaging Med Surg; 2024 Mar; 14(3):2485-2498. PubMed ID: 38545077
[TBL] [Abstract][Full Text] [Related]
38. Using Multi-phase CT Radiomics Features to Predict EGFR Mutation Status in Lung Adenocarcinoma Patients.
Zhang G; Man Q; Shang L; Zhang J; Cao Y; Li S; Qian R; Ren J; Pu H; Zhou J; Zhang Z; Kong W
Acad Radiol; 2024 Jan; ():. PubMed ID: 38290884
[TBL] [Abstract][Full Text] [Related]
39. Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics.
Huynh BN; Groendahl AR; Tomic O; Liland KH; Knudtsen IS; Hoebers F; van Elmpt W; Malinen E; Dale E; Futsaether CM
Front Med (Lausanne); 2023; 10():1217037. PubMed ID: 37711738
[TBL] [Abstract][Full Text] [Related]
40. Machine Learning-Based CT Radiomics Analysis for Prognostic Prediction in Metastatic Non-Small Cell Lung Cancer Patients With
Tang X; Li Y; Yan WF; Qian WL; Pang T; Gong YL; Yang ZG
Front Oncol; 2021; 11():719919. PubMed ID: 34660285
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
