BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

180 related articles for article (PubMed ID: 34545474)

  • 1. Machine Learning in the Differentiation of Soft Tissue Neoplasms: Comparison of Fat-Suppressed T2WI and Apparent Diffusion Coefficient (ADC) Features-Based Models.
    Hu P; Chen L; Zhou Z
    J Digit Imaging; 2021 Oct; 34(5):1146-1155. PubMed ID: 34545474
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Application of MR Imaging Characteristics in the Differentiation of Renal Changes Between Patients with Stage III Type 2 Diabetic Kidney Disease and Healthy People.
    Zhang H; Yu B; Yang H; Ying H; Qu X; Zhu L; Wang C; Ding J
    Diabetes Metab Syndr Obes; 2023; 16():2177-2186. PubMed ID: 37521748
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.
    Ji X; Zhang J; Shi W; He D; Bao J; Wei X; Huang Y; Liu Y; Chen JC; Gao X; Tang Y; Xia W
    Phys Eng Sci Med; 2021 Sep; 44(3):745-754. PubMed ID: 34075559
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application and Clinical Value of Machine Learning-Based Cervical Cancer Diagnosis and Prediction Model in Adjuvant Chemotherapy for Cervical Cancer: A Single-Center, Controlled, Non-Arbitrary Size Case-Control Study.
    Wang Y; Shen L; Jin J; Wang G
    Contrast Media Mol Imaging; 2022; 2022():2432291. PubMed ID: 35821886
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Performances of Whole Tumor Texture Analysis Based on MRI: Predicting Preoperative T Stage of Rectal Carcinomas.
    You J; Yin J
    Front Oncol; 2021; 11():678441. PubMed ID: 34414105
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Multi-Parametric Magnetic Resonance Imaging-Based Radiomics Analysis of Cervical Cancer for Preoperative Prediction of Lymphovascular Space Invasion.
    Huang G; Cui Y; Wang P; Ren J; Wang L; Ma Y; Jia Y; Ma X; Zhao L
    Front Oncol; 2021; 11():663370. PubMed ID: 35096556
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A radiomics method based on MR FS-T2WI sequence for diagnosing of autosomal dominant polycystic kidney disease progression.
    Cong L; Hua QQ; Huang ZQ; Ma QL; Wang XM; Huang CC; Xu JX; Ma T
    Eur Rev Med Pharmacol Sci; 2021 Sep; 25(18):5769-5780. PubMed ID: 34604968
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Value of conventional magnetic resonance imaging texture analysis in the differential diagnosis of benign and borderline/malignant phyllodes tumors of the breast.
    Li X; Jiang N; Zhang C; Luo X; Zhong P; Fang J
    Cancer Imaging; 2021 Mar; 21(1):29. PubMed ID: 33712070
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Ensemble learning-based radiomics with multi-sequence magnetic resonance imaging for benign and malignant soft tissue tumor differentiation.
    Lee S; Lee SY; Jung JY; Nam Y; Jeon HJ; Jung CK; Shin SH; Chung YG
    PLoS One; 2023; 18(5):e0286417. PubMed ID: 37256875
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Discriminating malignant from benign testicular masses using machine-learning based radiomics signature of appearance diffusion coefficient maps: Comparing with conventional mean and minimum ADC values.
    Fan C; Sun K; Min X; Cai W; Lv W; Ma X; Li Y; Chen C; Zhao P; Qiao J; Lu J; Guo Y; Xia L
    Eur J Radiol; 2022 Mar; 148():110158. PubMed ID: 35066342
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. [Application of Automated Machine Learning Based on Radiomics Features of T2WI and RS-EPI DWI to Predict Preoperative T Staging of Rectal Cancer].
    Wen DG; Hu SX; Li ZL; Deng XB; Tian C; Li X; Wang XR; Leng Q; Xia CC
    Sichuan Da Xue Xue Bao Yi Xue Ban; 2021 Jul; 52(4):698-705. PubMed ID: 34323052
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multiparametric MRI-based machine learning models for preoperatively predicting rectal adenoma with canceration.
    Li P; Song G; Wu R; Li H; Zhang R; Zuo P; Li A
    MAGMA; 2021 Oct; 34(5):707-716. PubMed ID: 33646452
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Experimental study of inflammatory and metastatic lymph nodes with diffusion weighted imaging on animal model: comparison with conventional methods.
    Xue HD; Li S; Sun HY; Jin ZY; Sun F
    Chin Med Sci J; 2008 Sep; 23(3):166-71. PubMed ID: 18853852
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development and validation of a logistic regression model to distinguish transition zone cancers from benign prostatic hyperplasia on multi-parametric prostate MRI.
    Iyama Y; Nakaura T; Katahira K; Iyama A; Nagayama Y; Oda S; Utsunomiya D; Yamashita Y
    Eur Radiol; 2017 Sep; 27(9):3600-3608. PubMed ID: 28289941
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of MR Imaging Features in Differentiation of Renal Changes in Patients With Stage III Type 2 Diabetic Nephropathy and Normal Subjects.
    Yu B; Huang C; Fan X; Li F; Zhang J; Song Z; Zhi N; Ding J
    Front Endocrinol (Lausanne); 2022; 13():846407. PubMed ID: 35600605
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Orbital Indeterminate Lesions in Adults: Combined Magnetic Resonance Morphometry and Histogram Analysis of Apparent Diffusion Coefficient Maps for Predicting Malignancy.
    Xu XQ; Hu H; Su GY; Zhang L; Liu H; Hong XN; Shi HB; Wu FY
    Acad Radiol; 2016 Feb; 23(2):200-8. PubMed ID: 26625705
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study.
    Jian L; Liu Y; Xie Y; Jiang S; Ye M; Lin H
    Front Oncol; 2022; 12():876664. PubMed ID: 35719934
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Diagnostic Usefulness of Combination of Diffusion-weighted Imaging and T2WI, Including Apparent Diffusion Coefficient in Breast Lesions: Assessment of Histologic Grade.
    Kim KW; Kuzmiak CM; Kim YJ; Seo JY; Jung HK; Lee MS
    Acad Radiol; 2018 May; 25(5):643-652. PubMed ID: 29339079
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Pretreatment MR imaging radiomics signatures for response prediction to induction chemotherapy in patients with nasopharyngeal carcinoma.
    Wang G; He L; Yuan C; Huang Y; Liu Z; Liang C
    Eur J Radiol; 2018 Jan; 98():100-106. PubMed ID: 29279146
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.