BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

320 related articles for article (PubMed ID: 35342074)

  • 1. Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.
    Luo Y; Li Y; Zhang Y; Zhang J; Liang M; Jiang L; Guo L
    J Xray Sci Technol; 2022; 30(3):477-490. PubMed ID: 35342074
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
    Wang X; Wan Q; Chen H; Li Y; Li X
    Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.
    Yin P; Mao N; Zhao C; Wu J; Sun C; Chen L; Hong N
    Eur Radiol; 2019 Apr; 29(4):1841-1847. PubMed ID: 30280245
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.
    Wan Q; Zhou J; Xia X; Hu J; Wang P; Peng Y; Zhang T; Sun J; Song Y; Yang G; Li X
    Front Oncol; 2021; 11():683587. PubMed ID: 34868905
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Potential of radiomics analysis and machine learning for predicting brain metastasis in newly diagnosed lung cancer patients.
    Yichu S; Fei L; Ying L; Youyou X
    Clin Radiol; 2024 Jun; 79(6):e807-e816. PubMed ID: 38395696
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
    Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
    Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An investigation of machine learning methods in delta-radiomics feature analysis.
    Chang Y; Lafata K; Sun W; Wang C; Chang Z; Kirkpatrick JP; Yin FF
    PLoS One; 2019; 14(12):e0226348. PubMed ID: 31834910
    [TBL] [Abstract][Full Text] [Related]  

  • 9. CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors.
    Zheng Y; Zhou D; Liu H; Wen M
    Eur Radiol; 2022 Oct; 32(10):6953-6964. PubMed ID: 35484339
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram.
    Liu A; Wang Z; Yang Y; Wang J; Dai X; Wang L; Lu Y; Xue F
    Cancer Commun (Lond); 2020 Jan; 40(1):16-24. PubMed ID: 32125097
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer.
    Choi W; Oh JH; Riyahi S; Liu CJ; Jiang F; Chen W; White C; Rimner A; Mechalakos JG; Deasy JO; Lu W
    Med Phys; 2018 Apr; 45(4):1537-1549. PubMed ID: 29457229
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning Methods for Optimal Radiomics-Based Differentiation Between Recurrence and Inflammation: Application to Nasopharyngeal Carcinoma Post-therapy PET/CT Images.
    Du D; Feng H; Lv W; Ashrafinia S; Yuan Q; Wang Q; Yang W; Feng Q; Chen W; Rahmim A; Lu L
    Mol Imaging Biol; 2020 Jun; 22(3):730-738. PubMed ID: 31338709
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. A combined non-enhanced CT radiomics and clinical variable machine learning model for differentiating benign and malignant sub-centimeter pulmonary solid nodules.
    Lin RY; Zheng YN; Lv FJ; Fu BJ; Li WJ; Liang ZR; Chu ZG
    Med Phys; 2023 May; 50(5):2835-2843. PubMed ID: 36810703
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [Application of Radiomics in Classification and Prediction of Benign and Malignant Lung Tumors].
    Zhou T; Zhu C; Shi F
    Zhongguo Yi Liao Qi Xie Za Zhi; 2020 Feb; 44(2):113-117. PubMed ID: 32400982
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Potential feature exploration and model development based on 18F-FDG PET/CT images for differentiating benign and malignant lung lesions.
    Zhang R; Zhu L; Cai Z; Jiang W; Li J; Yang C; Yu C; Jiang B; Wang W; Xu W; Chai X; Zhang X; Tang Y
    Eur J Radiol; 2019 Dec; 121():108735. PubMed ID: 31733432
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine learning based on SPECT/CT to differentiate bone metastasis and benign bone lesions in lung malignancy patients.
    Wang H; Chen Y; Qiu J; Xie J; Lu W; Ma J; Jia M
    Med Phys; 2024 Apr; 51(4):2578-2588. PubMed ID: 37966123
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics.
    Mao B; Ma J; Duan S; Xia Y; Tao Y; Zhang L
    Eur Radiol; 2021 Jul; 31(7):4576-4586. PubMed ID: 33447862
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR.
    Sun K; Jiao Z; Zhu H; Chai W; Yan X; Fu C; Cheng JZ; Yan F; Shen D
    J Transl Med; 2021 Oct; 19(1):443. PubMed ID: 34689804
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Radiomics-based machine learning in the differentiation of benign and malignant bowel wall thickening radiomics in bowel wall thickening.
    Bülbül HM; Burakgazi G; Kesimal U; Kaba E
    Jpn J Radiol; 2024 Mar; ():. PubMed ID: 38536559
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.