BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

137 related articles for article (PubMed ID: 38237479)

  • 1. Body composition radiomic features as a predictor of survival in patients with non-small cellular lung carcinoma: A multicenter retrospective study.
    Rozynek M; Tabor Z; Kłęk S; Wojciechowski W
    Nutrition; 2024 Apr; 120():112336. PubMed ID: 38237479
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Body Composition and Radiomics From 18 F-FDG PET/CT Together Help Predict Prognosis for Patients With Stage IV Non-Small Cell Lung Cancer.
    Zhang Y; Tan W; Zheng Z; Wang J; Xing L; Sun X
    J Comput Assist Tomogr; 2023 Nov-Dec 01; 47(6):906-912. PubMed ID: 37948365
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Pre-treatment
    Ahn HK; Lee H; Kim SG; Hyun SH
    Clin Radiol; 2019 Jun; 74(6):467-473. PubMed ID: 30898382
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer.
    Hyun SH; Ahn MS; Koh YW; Lee SJ
    Clin Nucl Med; 2019 Dec; 44(12):956-960. PubMed ID: 31689276
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. Plausibility and redundancy analysis to select FDG-PET textural features in non-small cell lung cancer.
    Pfaehler E; Mesotten L; Zhovannik I; Pieplenbosch S; Thomeer M; Vanhove K; Adriaensens P; Boellaard R
    Med Phys; 2021 Mar; 48(3):1226-1238. PubMed ID: 33368399
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomic signature as a diagnostic factor for histologic subtype classification of non-small cell lung cancer.
    Zhu X; Dong D; Chen Z; Fang M; Zhang L; Song J; Yu D; Zang Y; Liu Z; Shi J; Tian J
    Eur Radiol; 2018 Jul; 28(7):2772-2778. PubMed ID: 29450713
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Homology-based radiomic features for prediction of the prognosis of lung cancer based on CT-based radiomics.
    Kadoya N; Tanaka S; Kajikawa T; Tanabe S; Abe K; Nakajima Y; Yamamoto T; Takahashi N; Takeda K; Dobashi S; Takeda K; Nakane K; Jingu K
    Med Phys; 2020 Jun; 47(5):2197-2205. PubMed ID: 32096876
    [TBL] [Abstract][Full Text] [Related]  

  • 10. CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer.
    Wang J; Wang J; Huang X; Zhou Y; Qi J; Sun X; Nie J; Hu Z; Wang S; Hong B; Wang H
    BMC Med Imaging; 2024 Feb; 24(1):45. PubMed ID: 38360550
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery.
    Kirienko M; Cozzi L; Antunovic L; Lozza L; Fogliata A; Voulaz E; Rossi A; Chiti A; Sollini M
    Eur J Nucl Med Mol Imaging; 2018 Feb; 45(2):207-217. PubMed ID: 28944403
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pretherapy 18F-fluorodeoxyglucose positron emission tomography/computed tomography robust radiomic features predict overall survival in non-small cell lung cancer.
    Mostafa R; Abdelsamie Kandeel A; Abd Elkareem M; Nardo L; Abdelhafez YG
    Nucl Med Commun; 2022 May; 43(5):540-548. PubMed ID: 35190518
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Application of 18 F-fluorodeoxyglucose PET/CT radiomic features and machine learning to predict early recurrence of non-small cell lung cancer after curative-intent therapy.
    Park SB; Kim KU; Park YW; Hwang JH; Lim CH
    Nucl Med Commun; 2023 Feb; 44(2):161-168. PubMed ID: 36458424
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Radiomic-Based Pathological Response Prediction from Primary Tumors and Lymph Nodes in NSCLC.
    Coroller TP; Agrawal V; Huynh E; Narayan V; Lee SW; Mak RH; Aerts HJWL
    J Thorac Oncol; 2017 Mar; 12(3):467-476. PubMed ID: 27903462
    [TBL] [Abstract][Full Text] [Related]  

  • 16. CT radiomics-based long-term survival prediction for locally advanced non-small cell lung cancer patients treated with concurrent chemoradiotherapy using features from tumor and tumor organismal environment.
    Chen NB; Xiong M; Zhou R; Zhou Y; Qiu B; Luo YF; Zhou S; Chu C; Li QW; Wang B; Jiang HH; Guo JY; Peng KQ; Xie CM; Liu H
    Radiat Oncol; 2022 Nov; 17(1):184. PubMed ID: 36384755
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability.
    Qiu Q; Duan J; Duan Z; Meng X; Ma C; Zhu J; Lu J; Liu T; Yin Y
    Quant Imaging Med Surg; 2019 Mar; 9(3):453-464. PubMed ID: 31032192
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Application and limitation of radiomics approach to prognostic prediction for lung stereotactic body radiotherapy using breath-hold CT images with random survival forest: A multi-institutional study.
    Kakino R; Nakamura M; Mitsuyoshi T; Shintani T; Kokubo M; Negoro Y; Fushiki M; Ogura M; Itasaka S; Yamauchi C; Otsu S; Sakamoto T; Sakamoto M; Araki N; Hirashima H; Adachi T; Matsuo Y; Mizowaki T
    Med Phys; 2020 Sep; 47(9):4634-4643. PubMed ID: 32645224
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi-institutional dose-segmented dosiomic analysis for predicting radiation pneumonitis after lung stereotactic body radiation therapy.
    Adachi T; Nakamura M; Shintani T; Mitsuyoshi T; Kakino R; Ogata T; Ono T; Tanabe H; Kokubo M; Sakamoto T; Matsuo Y; Mizowaki T
    Med Phys; 2021 Apr; 48(4):1781-1791. PubMed ID: 33576510
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An [
    Meng N; Feng P; Yu X; Wu Y; Fu F; Li Z; Luo Y; Tan H; Yuan J; Yang Y; Wang Z; Wang M
    Eur Radiol; 2024 Jan; 34(1):318-329. PubMed ID: 37530809
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.