BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

239 related articles for article (PubMed ID: 36515713)

  • 1. 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]  

  • 2. Machine-learning-based contrast-enhanced computed tomography radiomic analysis for categorization of ovarian tumors.
    Li J; Zhang T; Ma J; Zhang N; Zhang Z; Ye Z
    Front Oncol; 2022; 12():934735. PubMed ID: 36016613
    [TBL] [Abstract][Full Text] [Related]  

  • 3. CT-Based Radiomics for the Preoperative Prediction of Occult Peritoneal Metastasis in Epithelial Ovarian Cancers.
    Li J; Zhang J; Wang F; Ma J; Cui S; Ye Z
    Acad Radiol; 2024 May; 31(5):1918-1930. PubMed ID: 38072725
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Contrast-enhanced CT radiomics for preoperative prediction of stage in epithelial ovarian cancer: a multicenter study.
    Leng Y; Kan A; Wang X; Li X; Xiao X; Wang Y; Liu L; Gong L
    BMC Cancer; 2024 Mar; 24(1):307. PubMed ID: 38448945
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multimodality radiomics prediction of radiotherapy-induced the early proctitis and cystitis in rectal cancer patients: a machine learning study.
    Abbaspour S; Barahman M; Abdollahi H; Arabalibeik H; Hajainfar G; Babaei M; Iraji H; Barzegartahamtan M; Ay MR; Mahdavi SR
    Biomed Phys Eng Express; 2023 Dec; 10(1):. PubMed ID: 37995359
    [No Abstract]   [Full Text] [Related]  

  • 6. 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]  

  • 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. Prediction of the Ki-67 expression level in head and neck squamous cell carcinoma with machine learning-based multiparametric MRI radiomics: a multicenter study.
    Chen W; Lin G; Chen Y; Cheng F; Li X; Ding J; Zhong Y; Kong C; Chen M; Xia S; Lu C; Ji J
    BMC Cancer; 2024 Apr; 24(1):418. PubMed ID: 38580939
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Enhanced computed tomography radiomics-based machine-learning methods for predicting the Fuhrman grades of renal clear cell carcinoma.
    Yin RH; Yang YC; Tang XQ; Shi HF; Duan SF; Pan CJ
    J Xray Sci Technol; 2021; 29(6):1149-1160. PubMed ID: 34657848
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Prediction of the activity of Crohn's disease based on CT radiomics combined with machine learning models.
    Li T; Liu Y; Guo J; Wang Y
    J Xray Sci Technol; 2022; 30(6):1155-1168. PubMed ID: 35988261
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis.
    Mukherjee S; Patra A; Khasawneh H; Korfiatis P; Rajamohan N; Suman G; Majumder S; Panda A; Johnson MP; Larson NB; Wright DE; Kline TL; Fletcher JG; Chari ST; Goenka AH
    Gastroenterology; 2022 Nov; 163(5):1435-1446.e3. PubMed ID: 35788343
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multiparameter MRI-based radiomics for preoperative prediction of extramural venous invasion in rectal cancer.
    Shu Z; Mao D; Song Q; Xu Y; Pang P; Zhang Y
    Eur Radiol; 2022 Feb; 32(2):1002-1013. PubMed ID: 34482429
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning model based on enhanced CT radiomics for the preoperative prediction of lymphovascular invasion in esophageal squamous cell carcinoma.
    Wang Y; Bai G; Huang M; Chen W
    Front Oncol; 2024; 14():1308317. PubMed ID: 38549935
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma.
    Ma Y; Gong Y; Qiu Q; Ma C; Yu S
    BMC Cancer; 2024 Mar; 24(1):363. PubMed ID: 38515051
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers.
    Jian J; Li Y; Pickhardt PJ; Xia W; He Z; Zhang R; Zhao S; Zhao X; Cai S; Zhang J; Zhang G; Jiang J; Zhang Y; Wang K; Lin G; Feng F; Wu X; Gao X; Qiang J
    Eur Radiol; 2021 Jan; 31(1):403-410. PubMed ID: 32743768
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.
    Hu J; Zhao Y; Li M; Liu Y; Wang F; Weng Q; You R; Cao D
    Eur J Radiol; 2020 May; 126():108929. PubMed ID: 32169748
    [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. CT-based radiomics research for discriminating the risk stratification of pheochromocytoma using different machine learning models: a multi-center study.
    Zhao J; Zhan Y; Zhou Y; Yang Z; Xiong X; Ye Y; Yao B; Xu S; Peng Y; Xiao X; Zeng X; Zuo M; Dai X; Gong L
    Abdom Radiol (NY); 2024 May; 49(5):1569-1583. PubMed ID: 38587628
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.