BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 37996894)

  • 1. Improving the prediction of Spreading Through Air Spaces (STAS) in primary lung cancer with a dynamic dual-delta hybrid machine learning model: a multicenter cohort study.
    Jin W; Shen L; Tian Y; Zhu H; Zou N; Zhang M; Chen Q; Dong C; Yang Q; Jiang L; Huang J; Yuan Z; Ye X; Luo Q
    Biomark Res; 2023 Nov; 11(1):102. PubMed ID: 37996894
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study.
    Cui Y; Zhang J; Li Z; Wei K; Lei Y; Ren J; Wu L; Shi Z; Meng X; Yang X; Gao X
    EClinicalMedicine; 2022 Apr; 46():101348. PubMed ID: 35340629
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Role of radiomics in predicting lung cancer spread through air spaces in a heterogeneous dataset.
    Bassi M; Russomando A; Vannucci J; Ciardiello A; Dolciami M; Ricci P; Pernazza A; D'Amati G; Mancini Terracciano C; Faccini R; Mantovani S; Venuta F; Voena C; Anile M
    Transl Lung Cancer Res; 2022 Apr; 11(4):560-571. PubMed ID: 35529792
    [TBL] [Abstract][Full Text] [Related]  

  • 4. CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma.
    Lin MW; Chen LW; Yang SM; Hsieh MS; Ou DX; Lee YH; Chen JS; Chang YC; Chen CM
    Ann Surg Oncol; 2024 Mar; 31(3):1536-1545. PubMed ID: 37957504
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 3D convolutional neural network model from contrast-enhanced CT to predict spread through air spaces in non-small cell lung cancer.
    Tao J; Liang C; Yin K; Fang J; Chen B; Wang Z; Lan X; Zhang J
    Diagn Interv Imaging; 2022 Nov; 103(11):535-544. PubMed ID: 35773100
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomics-based prediction for tumour spread through air spaces in stage I lung adenocarcinoma using machine learning.
    Chen D; She Y; Wang T; Xie H; Li J; Jiang G; Chen Y; Zhang L; Xie D; Chen C
    Eur J Cardiothorac Surg; 2020 Jul; 58(1):51-58. PubMed ID: 32011674
    [TBL] [Abstract][Full Text] [Related]  

  • 7. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.
    Jiang C; Luo Y; Yuan J; You S; Chen Z; Wu M; Wang G; Gong J
    Eur Radiol; 2020 Jul; 30(7):4050-4057. PubMed ID: 32112116
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Non-linear modifications enhance prediction of pathological response to pre-operative PD-1 blockade in lung cancer: A longitudinal hybrid radiological model.
    Jin W; Tian Y; Xuzhang W; Zhu H; Zou N; Shen L; Dong C; Yang Q; Jiang L; Huang J; Yuan Z; Ye X; Luo Q
    Pharmacol Res; 2023 Dec; 198():106992. PubMed ID: 37977237
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Computed Tomography Radiomics for Preoperative Prediction of Spread Through Air Spaces in the Early Stage of Surgically Resected Lung Adenocarcinomas.
    Suh YJ; Han K; Kwon Y; Kim H; Lee S; Hwang SH; Kim MH; Shin HJ; Lee CY; Shim HS
    Yonsei Med J; 2024 Mar; 65(3):163-173. PubMed ID: 38373836
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Preoperative CT-based radiomics combined with tumour spread through air spaces can accurately predict early recurrence of stage I lung adenocarcinoma: a multicentre retrospective cohort study.
    Wang Y; Ding Y; Liu X; Li X; Jia X; Li J; Zhang H; Song Z; Xu M; Ren J; Sun D
    Cancer Imaging; 2023 Sep; 23(1):83. PubMed ID: 37679806
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A short-term follow-up CT based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer.
    Gong J; Bao X; Wang T; Liu J; Peng W; Shi J; Wu F; Gu Y
    Oncoimmunology; 2022; 11(1):2028962. PubMed ID: 35096486
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
    Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
    EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Nomogram based on clinical characteristics and radiological features for the preoperative prediction of spread through air spaces in patients with clinical stage IA non-small cell lung cancer: a multicenter study.
    Wang Y; Lyu D; Zhang D; Hu L; Wu J; Tu W; Xiao Y; Fan L; Liu S
    Diagn Interv Radiol; 2023 Nov; 29(6):771-785. PubMed ID: 37724737
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Advances in the prediction of spread through air spaces with imaging in lung cancer: a narrative review.
    Wang Y; Lyu D; Fan L; Liu S
    Transl Cancer Res; 2023 Mar; 12(3):624-630. PubMed ID: 37033348
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The Value of CT-Based Radiomics for Predicting Spread Through Air Spaces in Stage IA Lung Adenocarcinoma.
    Han X; Fan J; Zheng Y; Ding C; Zhang X; Zhang K; Wang N; Jia X; Li Y; Liu J; Zheng J; Shi H
    Front Oncol; 2022; 12():757389. PubMed ID: 35880159
    [TBL] [Abstract][Full Text] [Related]  

  • 16. The CT delta-radiomics based machine learning approach in evaluating multiple primary lung adenocarcinoma.
    Ma Y; Li J; Xu X; Zhang Y; Lin Y
    BMC Cancer; 2022 Sep; 22(1):949. PubMed ID: 36057553
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Use of radiomics based on
    Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
    Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Computer-aided diagnosis of distal metastasis in non-small cell lung cancer by low-dose CT based radiomics and deep learning signatures.
    Song X; Duan X; He X; Wang Y; Li K; Deng B; Chen X; Wang Y; Li M; Shan H
    Radiol Med; 2024 Feb; 129(2):239-251. PubMed ID: 38214839
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Peritumoral radiomics features on preoperative thin-slice CT images can predict the spread through air spaces of lung adenocarcinoma.
    Takehana K; Sakamoto R; Fujimoto K; Matsuo Y; Nakajima N; Yoshizawa A; Menju T; Nakamura M; Yamada R; Mizowaki T; Nakamoto Y
    Sci Rep; 2022 Jun; 12(1):10323. PubMed ID: 35725754
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.
    Ma X; Xia L; Chen J; Wan W; Zhou W
    Eur Radiol; 2023 Mar; 33(3):1949-1962. PubMed ID: 36169691
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.