BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

581 related articles for article (PubMed ID: 35484339)

  • 1. 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]  

  • 2. Comparison of Different Machine Models Based on Multi-Phase Computed Tomography Radiomic Analysis to Differentiate Parotid Basal Cell Adenoma From Pleomorphic Adenoma.
    Zheng YL; Zheng YN; Li CF; Gao JN; Zhang XY; Li XY; Zhou D; Wen M
    Front Oncol; 2022; 12():889833. PubMed ID: 35903689
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Multiphasic CT-Based Radiomics Analysis for the Differentiation of Benign and Malignant Parotid Tumors.
    Yu Q; Wang A; Gu J; Li Q; Ning Y; Peng J; Lv F; Zhang X
    Front Oncol; 2022; 12():913898. PubMed ID: 35847942
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Development and validation of CT-based radiomics nomogram for the classification of benign parotid gland tumors.
    Zheng M; Chen Q; Ge Y; Yang L; Tian Y; Liu C; Wang P; Deng K
    Med Phys; 2023 Feb; 50(2):947-957. PubMed ID: 36273307
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The Role of Preoperative Computed Tomography Radiomics in Distinguishing Benign and Malignant Tumors of the Parotid Gland.
    Xu Y; Shu Z; Song G; Liu Y; Pang P; Wen X; Gong X
    Front Oncol; 2021; 11():634452. PubMed ID: 33777789
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep learning-assisted diagnosis of benign and malignant parotid tumors based on contrast-enhanced CT: a multicenter study.
    Yu Q; Ning Y; Wang A; Li S; Gu J; Li Q; Chen X; Lv F; Zhang X; Yue Q; Peng J
    Eur Radiol; 2023 Sep; 33(9):6054-6065. PubMed ID: 37067576
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Development and Validation of Contrast-Enhanced CT-Based Deep Transfer Learning and Combined Clinical-Radiomics Model to Discriminate Thymomas and Thymic Cysts: A Multicenter Study.
    Yang Y; Cheng J; Peng Z; Yi L; Lin Z; He A; Jin M; Cui C; Liu Y; Zhong Q; Zuo M
    Acad Radiol; 2024 Apr; 31(4):1615-1628. PubMed ID: 37949702
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Leveraging multimodal MRI-based radiomics analysis with diverse machine learning models to evaluate lymphovascular invasion in clinically node-negative breast cancer.
    Jiang Y; Zeng Y; Zuo Z; Yang X; Liu H; Zhou Y; Fan X
    Heliyon; 2024 Jan; 10(1):e23916. PubMed ID: 38192872
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Computed tomography-based radiomics machine learning classifiers to differentiate type I and type II epithelial ovarian cancers.
    Li J; Li X; Ma J; Wang F; Cui S; Ye Z
    Eur Radiol; 2023 Jul; 33(7):5193-5204. PubMed ID: 36515713
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Development of a combined radiomics and CT feature-based model for differentiating malignant from benign subcentimeter solid pulmonary nodules.
    Liu J; Qi L; Wang Y; Li F; Chen J; Cui S; Cheng S; Zhou Z; Li L; Wang J
    Eur Radiol Exp; 2024 Jan; 8(1):8. PubMed ID: 38228868
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
    Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
    Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
    [TBL] [Abstract][Full Text] [Related]  

  • 12. CT-based radiomics analysis of different machine learning models for differentiating gnathic fibrous dysplasia and ossifying fibroma.
    Zhang AB; Zhao JR; Wang S; Xue J; Zhang JY; Sun ZP; Sun LS; Li TJ
    Oral Dis; 2024 May; ():. PubMed ID: 38813877
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine learning-based radiomics for histological classification of parotid tumors using morphological MRI: a comparative study.
    He Z; Mao Y; Lu S; Tan L; Xiao J; Tan P; Zhang H; Li G; Yan H; Tan J; Huang D; Qiu Y; Zhang X; Wang X; Liu Y
    Eur Radiol; 2022 Dec; 32(12):8099-8110. PubMed ID: 35748897
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A diagnostic approach integrated multimodal radiomics with machine learning models based on lumbar spine CT and X-ray for osteoporosis.
    Cheng L; Cai F; Xu M; Liu P; Liao J; Zong S
    J Bone Miner Metab; 2023 Nov; 41(6):877-889. PubMed ID: 37898574
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Preoperative contrast-enhanced CT-based radiomics nomogram for differentiating benign and malignant primary retroperitoneal tumors.
    Xu J; Guo J; Yang HQ; Ji QL; Song RJ; Hou F; Liang HY; Liu SL; Tian LT; Wang HX
    Eur Radiol; 2023 Oct; 33(10):6781-6793. PubMed ID: 37148350
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Differentiation of benign and malignant parotid gland tumors based on the fusion of radiomics and deep learning features on ultrasound images.
    Wang Y; Gao J; Yin Z; Wen Y; Sun M; Han R
    Front Oncol; 2024; 14():1384105. PubMed ID: 38803533
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Epithelial salivary gland tumors: Utility of radiomics analysis based on diffusion-weighted imaging for differentiation of benign from malignant tumors.
    Shao S; Mao N; Liu W; Cui J; Xue X; Cheng J; Zheng N; Wang B
    J Xray Sci Technol; 2020; 28(4):799-808. PubMed ID: 32538891
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Enhanced CT-based texture analysis and radiomics score for differentiation of pleomorphic adenoma, basal cell adenoma, and Warthin tumor of the parotid gland.
    Chen F; Ge Y; Li S; Liu M; Wu J; Liu Y
    Dentomaxillofac Radiol; 2023 Jan; 52(2):20220009. PubMed ID: 36367128
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Optimizing the radiomics-machine-learning model based on non-contrast enhanced CT for the simplified risk categorization of thymic epithelial tumors: A large cohort retrospective study.
    Feng XL; Wang SZ; Chen HH; Huang YX; Xin YK; Zhang T; Cheng DL; Mao L; Li XL; Liu CX; Hu YC; Wang W; Cui GB; Nan HY
    Lung Cancer; 2022 Apr; 166():150-160. PubMed ID: 35287067
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning for differentiation of lipid-poor adrenal adenoma and subclinical pheochromocytoma based on multiphase CT imaging radiomics.
    Xiao DX; Zhong JP; Peng JD; Fan CG; Wang XC; Wen XL; Liao WW; Wang J; Yin XF
    BMC Med Imaging; 2023 Oct; 23(1):159. PubMed ID: 37845636
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 30.