341 related articles for article (PubMed ID: 32486314)
1. Imaging-Based Prediction of Molecular Therapy Targets in NSCLC by Radiogenomics and AI Approaches: A Systematic Review.
Ninatti G; Kirienko M; Neri E; Sollini M; Chiti A
Diagnostics (Basel); 2020 May; 10(6):. PubMed ID: 32486314
[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. 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]
4. A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts ALK Rearrangement Status in Lung Adenocarcinoma.
Chang C; Sun X; Wang G; Yu H; Zhao W; Ge Y; Duan S; Qian X; Wang R; Lei B; Wang L; Liu L; Ruan M; Yan H; Liu C; Chen J; Xie W
Front Oncol; 2021; 11():603882. PubMed ID: 33738250
[TBL] [Abstract][Full Text] [Related]
5. The prognostic role of PD-1, PD-L1, ALK, and ROS1 proteins expression in non-small cell lung carcinoma patients from Egypt.
Bahnassy AA; Ismail H; Mohanad M; El-Bastawisy A; Yousef HF
J Egypt Natl Canc Inst; 2022 May; 34(1):23. PubMed ID: 35644823
[TBL] [Abstract][Full Text] [Related]
6. PET/CT Radiomic Features: A Potential Biomarker for EGFR Mutation Status and Survival Outcome Prediction in NSCLC Patients Treated With TKIs.
Yang L; Xu P; Li M; Wang M; Peng M; Zhang Y; Wu T; Chu W; Wang K; Meng H; Zhang L
Front Oncol; 2022; 12():894323. PubMed ID: 35800046
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Evaluating Solid Lung Adenocarcinoma Anaplastic Lymphoma Kinase Gene Rearrangement Using Noninvasive Radiomics Biomarkers.
Ma DN; Gao XY; Dan YB; Zhang AN; Wang WJ; Yang G; Zhu HZ
Onco Targets Ther; 2020; 13():6927-6935. PubMed ID: 32764984
[TBL] [Abstract][Full Text] [Related]
10. Assessing PD-L1 Expression Level by Radiomic Features From PET/CT in Nonsmall Cell Lung Cancer Patients: An Initial Result.
Jiang M; Sun D; Guo Y; Guo Y; Xiao J; Wang L; Yao X
Acad Radiol; 2020 Feb; 27(2):171-179. PubMed ID: 31147234
[TBL] [Abstract][Full Text] [Related]
11. Integration of comprehensive genomic profiling, tumor mutational burden, and PD-L1 expression to identify novel biomarkers of immunotherapy in non-small cell lung cancer.
Shi Y; Lei Y; Liu L; Zhang S; Wang W; Zhao J; Zhao S; Dong X; Yao M; Wang K; Zhou Q
Cancer Med; 2021 Apr; 10(7):2216-2231. PubMed ID: 33655698
[TBL] [Abstract][Full Text] [Related]
12. Molecular typing of lung adenocarcinoma with computed tomography and CT image-based radiomics: a narrative review of research progress and prospects.
Ma JW; Li M
Transl Cancer Res; 2021 Sep; 10(9):4217-4231. PubMed ID: 35116717
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Predicting EGFR and PD-L1 Status in NSCLC Patients Using Multitask AI System Based on CT Images.
Wang C; Ma J; Shao J; Zhang S; Liu Z; Yu Y; Li W
Front Immunol; 2022; 13():813072. PubMed ID: 35250988
[TBL] [Abstract][Full Text] [Related]
15.
Yang B; Ji HS; Zhou CS; Dong H; Ma L; Ge YQ; Zhu CH; Tian JH; Zhang LJ; Zhu H; Lu GM
Transl Lung Cancer Res; 2020 Jun; 9(3):563-574. PubMed ID: 32676320
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. 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]
18. Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas.
Yoon J; Suh YJ; Han K; Cho H; Lee HJ; Hur J; Choi BW
Thorac Cancer; 2020 Apr; 11(4):993-1004. PubMed ID: 32043309
[TBL] [Abstract][Full Text] [Related]
19. Artificial Intelligence in Breast Cancer: A Systematic Review on PET Imaging Clinical Applications.
Alongi P; Rovera G; Stracuzzi F; Popescu CE; Minutoli F; Arnone G; Baldari S; Deandreis D; Caobelli F
Curr Med Imaging; 2023; 19(8):832-843. PubMed ID: 36703586
[TBL] [Abstract][Full Text] [Related]
20. CT radiomics-based prediction of anaplastic lymphoma kinase and epidermal growth factor receptor mutations in lung adenocarcinoma.
Choe J; Lee SM; Kim W; Do KH; Kim S; Choi S; Seo JB
Eur J Radiol; 2021 Jun; 139():109710. PubMed ID: 33862316
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]