BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

176 related articles for article (PubMed ID: 36180806)

  • 21. Meningioma consistency assessment based on the fusion of deep learning features and radiomics features.
    Zhang J; Zhao Y; Lu Y; Li P; Dang S; Li X; Yin B; Zhao L
    Eur J Radiol; 2024 Jan; 170():111250. PubMed ID: 38071910
    [TBL] [Abstract][Full Text] [Related]  

  • 22. The value of an apparent diffusion coefficient histogram model in predicting meningioma recurrence.
    Han T; Liu X; Jing M; Zhang Y; Deng L; Zhang B; Zhou J
    J Cancer Res Clin Oncol; 2023 Dec; 149(19):17427-17436. PubMed ID: 37878091
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A Magnetic Resonance Imaging-Based Radiomic Model for the Noninvasive Preoperative Differentiation Between Transitional and Atypical Meningiomas.
    Zhang J; Zhang G; Cao Y; Ren J; Zhao Z; Han T; Chen K; Zhou J
    Front Oncol; 2022; 12():811767. PubMed ID: 35127543
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Predicting meningioma grades and pathologic marker expression via deep learning.
    Chen J; Xue Y; Ren L; Lv K; Du P; Cheng H; Sun S; Hua L; Xie Q; Wu R; Gong Y
    Eur Radiol; 2024 May; 34(5):2997-3008. PubMed ID: 37853176
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Radiomic Features of the Edema Region May Contribute to Grading Meningiomas With Peritumoral Edema.
    Guo Z; Tian Z; Shi F; Xu P; Zhang J; Ling C; Zeng Q
    J Magn Reson Imaging; 2023 Jul; 58(1):301-310. PubMed ID: 36259547
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Diagnostic nomogram model for predicting preoperative pathological grade of meningioma.
    Peng S; Cheng Z; Guo Z
    Transl Cancer Res; 2021 Sep; 10(9):4057-4064. PubMed ID: 35116703
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A nomogram for predicting the risk of major postoperative complications for patients with meningioma.
    Guo ZQ; Xia XY; Cao D; Chen X; He Y; Wang BF; Guo DS; Chen J
    Neurosurg Rev; 2023 Oct; 46(1):288. PubMed ID: 37907646
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Intratumoral and Peritumoral Analysis of Mammography, Tomosynthesis, and Multiparametric MRI for Predicting Ki-67 Level in Breast Cancer: a Radiomics-Based Study.
    Jiang T; Song J; Wang X; Niu S; Zhao N; Dong Y; Wang X; Luo Y; Jiang X
    Mol Imaging Biol; 2022 Aug; 24(4):550-559. PubMed ID: 34904187
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Multiparametric MRI-Based Radiomics Nomogram for Predicting Lymphovascular Space Invasion in Endometrial Carcinoma.
    Luo Y; Mei D; Gong J; Zuo M; Guo X
    J Magn Reson Imaging; 2020 Oct; 52(4):1257-1262. PubMed ID: 32315482
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Can CT and MRI features differentiate benign from malignant meningiomas?
    Salah F; Tabbarah A; ALArab Y N; Asmar K; Tamim H; Makki M; Sibahi A; Hourani R
    Clin Radiol; 2019 Nov; 74(11):898.e15-898.e23. PubMed ID: 31474303
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Base MRI Imaging Characteristics of Meningioma Patients to Discuss the WHO Classification of Brain Invasion Otherwise Benign Meningiomas.
    Luo X; Jiang H; Liu XJ; Zhang Z; Deng K; Lin F; Jiang J; Wang YL; Yu J
    Technol Cancer Res Treat; 2023; 22():15330338231171470. PubMed ID: 37264676
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Radiomic nomogram based on MRI to predict grade of branching type intraductal papillary mucinous neoplasms of the pancreas: a multicenter study.
    Cui S; Tang T; Su Q; Wang Y; Shu Z; Yang W; Gong X
    Cancer Imaging; 2021 Mar; 21(1):26. PubMed ID: 33750453
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Development and external validation of an MRI-based radiomics nomogram for pretreatment prediction for early relapse in osteosarcoma: A retrospective multicenter study.
    Chen H; Liu J; Cheng Z; Lu X; Wang X; Lu M; Li S; Xiang Z; Zhou Q; Liu Z; Zhao Y
    Eur J Radiol; 2020 Aug; 129():109066. PubMed ID: 32502729
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A nomogram for individual prediction of vascular invasion in primary breast cancer.
    Ouyang FS; Guo BL; Huang XY; Ouyang LZ; Zhou CR; Zhang R; Wu ML; Yang ZS; Wu SK; Guo TD; Yang SM; Hu QG
    Eur J Radiol; 2019 Jan; 110():30-38. PubMed ID: 30599870
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.
    Yu Y; Tan Y; Xie C; Hu Q; Ouyang J; Chen Y; Gu Y; Li A; Lu N; He Z; Yang Y; Chen K; Ma J; Li C; Ma M; Li X; Zhang R; Zhong H; Ou Q; Zhang Y; He Y; Li G; Wu Z; Su F; Song E; Yao H
    JAMA Netw Open; 2020 Dec; 3(12):e2028086. PubMed ID: 33289845
    [TBL] [Abstract][Full Text] [Related]  

  • 36. A Nomogram Model for Stratifying the Risk of Recurrence in Patients with Meningioma After Surgery.
    Mo G; Jiang Q; Bao Y; Deng T; Mo L; Huang Q
    World Neurosurg; 2023 Aug; 176():e644-e650. PubMed ID: 37271256
    [TBL] [Abstract][Full Text] [Related]  

  • 37. A Novel Nomogram to Identify Candidates for Extended Pelvic Lymph Node Dissection Among Patients with Clinically Localized Prostate Cancer Diagnosed with Magnetic Resonance Imaging-targeted and Systematic Biopsies.
    Gandaglia G; Ploussard G; Valerio M; Mattei A; Fiori C; Fossati N; Stabile A; Beauval JB; Malavaud B; Roumiguié M; Robesti D; Dell'Oglio P; Moschini M; Zamboni S; Rakauskas A; De Cobelli F; Porpiglia F; Montorsi F; Briganti A
    Eur Urol; 2019 Mar; 75(3):506-514. PubMed ID: 30342844
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Machine learning analyses can differentiate meningioma grade by features on magnetic resonance imaging.
    Hale AT; Stonko DP; Wang L; Strother MK; Chambless LB
    Neurosurg Focus; 2018 Nov; 45(5):E4. PubMed ID: 30453458
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.
    Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y
    Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions.
    Sun K; Zhang J; Liu Z; Qiu Q; Gao H; Liu P; Chen K; Wei W; Wang L; Zhang J; Zhou J; Tian J
    Eur J Radiol; 2022 Apr; 149():110187. PubMed ID: 35183900
    [TBL] [Abstract][Full Text] [Related]  

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