BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1035 related articles for article (PubMed ID: 32096876)

  • 1. 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]  

  • 2. Impact of feature selection methods and subgroup factors on prognostic analysis with CT-based radiomics in non-small cell lung cancer patients.
    Sugai Y; Kadoya N; Tanaka S; Tanabe S; Umeda M; Yamamoto T; Takeda K; Dobashi S; Ohashi H; Takeda K; Jingu K
    Radiat Oncol; 2021 Apr; 16(1):80. PubMed ID: 33931085
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Combination of computed tomography imaging-based radiomics and clinicopathological characteristics for predicting the clinical benefits of immune checkpoint inhibitors in lung cancer.
    Yang B; Zhou L; Zhong J; Lv T; Li A; Ma L; Zhong J; Yin S; Huang L; Zhou C; Li X; Ge YQ; Tao X; Zhang L; Son Y; Lu G
    Respir Res; 2021 Jun; 22(1):189. PubMed ID: 34183009
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Homological radiomics analysis for prognostic prediction in lung cancer patients.
    Ninomiya K; Arimura H
    Phys Med; 2020 Jan; 69():90-100. PubMed ID: 31855844
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Identification of optimal mother wavelets in survival prediction of lung cancer patients using wavelet decomposition-based radiomic features.
    Soufi M; Arimura H; Nagami N
    Med Phys; 2018 Nov; 45(11):5116-5128. PubMed ID: 30230556
    [TBL] [Abstract][Full Text] [Related]  

  • 7. CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer.
    Huynh E; Coroller TP; Narayan V; Agrawal V; Hou Y; Romano J; Franco I; Mak RH; Aerts HJ
    Radiother Oncol; 2016 Aug; 120(2):258-66. PubMed ID: 27296412
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Classification of early stage non-small cell lung cancers on computed tomographic images into histological types using radiomic features: interobserver delineation variability analysis.
    Haga A; Takahashi W; Aoki S; Nawa K; Yamashita H; Abe O; Nakagawa K
    Radiol Phys Technol; 2018 Mar; 11(1):27-35. PubMed ID: 29209915
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images.
    van Timmeren JE; Leijenaar RTH; van Elmpt W; Reymen B; Oberije C; Monshouwer R; Bussink J; Brink C; Hansen O; Lambin P
    Radiother Oncol; 2017 Jun; 123(3):363-369. PubMed ID: 28506693
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Longitudinal radiomics of cone-beam CT images from non-small cell lung cancer patients: Evaluation of the added prognostic value for overall survival and locoregional recurrence.
    van Timmeren JE; van Elmpt W; Leijenaar RTH; Reymen B; Monshouwer R; Bussink J; Paelinck L; Bogaert E; De Wagter C; Elhaseen E; Lievens Y; Hansen O; Brink C; Lambin P
    Radiother Oncol; 2019 Jul; 136():78-85. PubMed ID: 31015133
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-level multi-modality (PET and CT) fusion radiomics: prognostic modeling for non-small cell lung carcinoma.
    Amini M; Nazari M; Shiri I; Hajianfar G; Deevband MR; Abdollahi H; Arabi H; Rahmim A; Zaidi H
    Phys Med Biol; 2021 Oct; 66(20):. PubMed ID: 34544053
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Performance of radiomics models for survival prediction in non-small-cell lung cancer: influence of CT slice thickness.
    Park S; Lee SM; Kim S; Choi S; Kim W; Do KH; Seo JB
    Eur Radiol; 2021 May; 31(5):2856-2865. PubMed ID: 33128185
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Integrative nomogram of CT imaging, clinical, and hematological features for survival prediction of patients with locally advanced non-small cell lung cancer.
    Wang L; Dong T; Xin B; Xu C; Guo M; Zhang H; Feng D; Wang X; Yu J
    Eur Radiol; 2019 Jun; 29(6):2958-2967. PubMed ID: 30643940
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis.
    Sun W; Jiang M; Dang J; Chang P; Yin FF
    Radiat Oncol; 2018 Oct; 13(1):197. PubMed ID: 30290849
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients.
    Yang L; Yang J; Zhou X; Huang L; Zhao W; Wang T; Zhuang J; Tian J
    Eur Radiol; 2019 May; 29(5):2196-2206. PubMed ID: 30523451
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Effectiveness of CT radiomic features combined with clinical factors in predicting prognosis in patients with limited-stage small cell lung cancer.
    Wu J; Zhou Y; Xu C; Yang C; Liu B; Zhao L; Song J; Wang W; Yang Y; Liu N
    BMC Cancer; 2024 Feb; 24(1):170. PubMed ID: 38310283
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Investigation of thoracic four-dimensional CT-based dimension reduction technique for extracting the robust radiomic features.
    Tanaka S; Kadoya N; Kajikawa T; Matsuda S; Dobashi S; Takeda K; Jingu K
    Phys Med; 2019 Feb; 58():141-148. PubMed ID: 30824145
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 52.