BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

162 related articles for article (PubMed ID: 37725128)

  • 21. Prognostic role of positron emission tomography and high-resolution computed tomography in clinical stage IA lung adenocarcinoma.
    Uehara H; Tsutani Y; Okumura S; Nakayama H; Adachi S; Yoshimura M; Miyata Y; Okada M
    Ann Thorac Surg; 2013 Dec; 96(6):1958-65. PubMed ID: 24021765
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules.
    Chen X; Feng B; Chen Y; Liu K; Li K; Duan X; Hao Y; Cui E; Liu Z; Zhang C; Long W; Liu X
    Cancer Imaging; 2020 Jul; 20(1):45. PubMed ID: 32641166
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Occult mediastinal lymph node metastasis in FDG-PET/CT node-negative lung adenocarcinoma patients: Risk factors and histopathological study.
    Miao H; Shaolei L; Nan L; Yumei L; Shanyuan Z; Fangliang L; Yue Y
    Thorac Cancer; 2019 Jun; 10(6):1453-1460. PubMed ID: 31127706
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Computed Tomography-based Prognostication in Lung Adenocarcinomas through Histopathological Feature Learning: A Retrospective Multicenter Study.
    Lee KH; Lee JH; Park S; Jeon YK; Chung DH; Kim YT; Goo JM; Kim H
    Ann Am Thorac Soc; 2023 Jul; 20(7):1020-1028. PubMed ID: 37075305
    [No Abstract]   [Full Text] [Related]  

  • 25. 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]  

  • 26. Computed Tomography and
    Kawaguchi M; Kato H; Hanamatsu Y; Suto T; Noda Y; Kaneko Y; Iwata H; Hyodo F; Miyazaki T; Matsuo M
    Clin Oncol (R Coll Radiol); 2023 Oct; 35(10):e601-e610. PubMed ID: 37587000
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.
    Lue KH; Chen YH; Chu SC; Chang BS; Lin CB; Chen YC; Lin HH; Liu SH
    Nucl Med Commun; 2023 Dec; 44(12):1094-1105. PubMed ID: 37728592
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans.
    Wang X; Zhang L; Yang X; Tang L; Zhao J; Chen G; Li X; Yan S; Li S; Yang Y; Kang Y; Li Q; Wu N
    Eur J Radiol; 2020 Aug; 129():109150. PubMed ID: 32604042
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Prognostic role of positron emission tomography and computed tomography parameters in stage I lung adenocarcinoma.
    Carretta A; Bandiera A; Muriana P; Viscardi S; Ciriaco P; Gajate AMS; Arrigoni G; Lazzari C; Gregorc V; Negri G
    Radiol Oncol; 2020 May; 54(3):278-284. PubMed ID: 32463388
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Outcome prediction in resectable lung adenocarcinoma patients: value of CT radiomics.
    Choe J; Lee SM; Do KH; Kim S; Choi S; Lee JG; Seo JB
    Eur Radiol; 2020 Sep; 30(9):4952-4963. PubMed ID: 32356158
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Machine learning based on clinico-biological features integrated
    Ren C; Zhang J; Qi M; Zhang J; Zhang Y; Song S; Sun Y; Cheng J
    Eur J Nucl Med Mol Imaging; 2021 May; 48(5):1538-1549. PubMed ID: 33057772
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma.
    Chang C; Zhou S; Yu H; Zhao W; Ge Y; Duan S; Wang R; Qian X; Lei B; Wang L; Liu L; Ruan M; Yan H; Sun X; Xie W
    Eur Radiol; 2021 Aug; 31(8):6259-6268. PubMed ID: 33544167
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.
    Feng B; Chen X; Chen Y; Lu S; Liu K; Li K; Liu Z; Hao Y; Li Z; Zhu Z; Yao N; Liang G; Zhang J; Long W; Liu X
    Eur Radiol; 2020 Dec; 30(12):6497-6507. PubMed ID: 32594210
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.
    Zhong Y; She Y; Deng J; Chen S; Wang T; Yang M; Ma M; Song Y; Qi H; Wang Y; Shi J; Wu C; Xie D; Chen C;
    Radiology; 2022 Jan; 302(1):200-211. PubMed ID: 34698568
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.
    Huang H; Zheng D; Chen H; Wang Y; Chen C; Xu L; Li G; Wang Y; He X; Li W
    Med Phys; 2022 Oct; 49(10):6384-6394. PubMed ID: 35938604
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Long-Term Outcomes After Sublobar Resection Versus Lobectomy in Patients With Clinical Stage IA Lung Adenocarcinoma Meeting the Node-Negative Criteria Defined by High-Resolution Computed Tomography and [
    Tsutani Y; Nakayama H; Ito H; Handa Y; Mimae T; Miyata Y; Okada M
    Clin Lung Cancer; 2021 May; 22(3):e431-e437. PubMed ID: 32665166
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma.
    Nie P; Yang G; Wang N; Yan L; Miao W; Duan Y; Wang Y; Gong A; Zhao Y; Wu J; Zhang C; Wang M; Cui J; Yu M; Li D; Sun Y; Wang Y; Wang Z
    Eur J Nucl Med Mol Imaging; 2021 Jan; 48(1):217-230. PubMed ID: 32451603
    [TBL] [Abstract][Full Text] [Related]  

  • 38. The predictive value of CT-based radiomics in differentiating indolent from invasive lung adenocarcinoma in patients with pulmonary nodules.
    She Y; Zhang L; Zhu H; Dai C; Xie D; Xie H; Zhang W; Zhao L; Zou L; Fei K; Sun X; Chen C
    Eur Radiol; 2018 Dec; 28(12):5121-5128. PubMed ID: 29869172
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Computed Tomography-Based Radiomics Signature: A Potential Indicator of Epidermal Growth Factor Receptor Mutation in Pulmonary Adenocarcinoma Appearing as a Subsolid Nodule.
    Yang X; Dong X; Wang J; Li W; Gu Z; Gao D; Zhong N; Guan Y
    Oncologist; 2019 Nov; 24(11):e1156-e1164. PubMed ID: 30936378
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A pretreatment prediction model of grade 3 tumors classed by the IASLC grading system in lung adenocarcinoma.
    Wang K; Liu X; Ding Y; Sun S; Li J; Geng H; Xu M; Wang M; Li X; Sun D
    BMC Pulm Med; 2023 Oct; 23(1):377. PubMed ID: 37805451
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.