BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

141 related articles for article (PubMed ID: 36341993)

  • 61. Utility of Ultrasonography for Diagnosis of Salivary Gland Sialolithiasis: A Meta-Analysis.
    Kim DH; Kang JM; Kim SW; Kim SH; Jung JH; Hwang SH
    Laryngoscope; 2022 Sep; 132(9):1785-1791. PubMed ID: 35043982
    [TBL] [Abstract][Full Text] [Related]  

  • 62. Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma.
    Lu Y; Patel M; Natarajan K; Ughratdar I; Sanghera P; Jena R; Watts C; Sawlani V
    Magn Reson Imaging; 2020 Dec; 74():161-170. PubMed ID: 32980505
    [TBL] [Abstract][Full Text] [Related]  

  • 63. Machine learning in the differentiation of follicular lymphoma from diffuse large B-cell lymphoma with radiomic [
    de Jesus FM; Yin Y; Mantzorou-Kyriaki E; Kahle XU; de Haas RJ; Yakar D; Glaudemans AWJM; Noordzij W; Kwee TC; Nijland M
    Eur J Nucl Med Mol Imaging; 2022 Apr; 49(5):1535-1543. PubMed ID: 34850248
    [TBL] [Abstract][Full Text] [Related]  

  • 64. 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]  

  • 65. Submandibular salivary gland volume is increased in patients with acromegaly.
    Manetti L; Bogazzi F; Brogioni S; Grasso L; Lupi I; Genovesi M; Cecconi E; Gasperi M; Martino E
    Clin Endocrinol (Oxf); 2002 Jul; 57(1):97-100. PubMed ID: 12100076
    [TBL] [Abstract][Full Text] [Related]  

  • 66. Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings.
    Shiradkar R; Ghose S; Jambor I; Taimen P; Ettala O; Purysko AS; Madabhushi A
    J Magn Reson Imaging; 2018 Dec; 48(6):1626-1636. PubMed ID: 29734484
    [TBL] [Abstract][Full Text] [Related]  

  • 67. A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts ALK Rearrangement Status in Lung Adenocarcinoma.
    Chang C; Sun X; Wang G; Yu H; Zhao W; Ge Y; Duan S; Qian X; Wang R; Lei B; Wang L; Liu L; Ruan M; Yan H; Liu C; Chen J; Xie W
    Front Oncol; 2021; 11():603882. PubMed ID: 33738250
    [TBL] [Abstract][Full Text] [Related]  

  • 68. Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets.
    McNitt-Gray M; Napel S; Jaggi A; Mattonen SA; Hadjiiski L; Muzi M; Goldgof D; Balagurunathan Y; Pierce LA; Kinahan PE; Jones EF; Nguyen A; Virkud A; Chan HP; Emaminejad N; Wahi-Anwar M; Daly M; Abdalah M; Yang H; Lu L; Lv W; Rahmim A; Gastounioti A; Pati S; Bakas S; Kontos D; Zhao B; Kalpathy-Cramer J; Farahani K
    Tomography; 2020 Jun; 6(2):118-128. PubMed ID: 32548288
    [TBL] [Abstract][Full Text] [Related]  

  • 69. Identification of reproducible radiomic features from on-board volumetric images: A multi-institutional phantom study.
    Adachi T; Nakamura M; Iramina H; Matsumoto K; Ishihara Y; Tachibana H; Kurokawa S; Cho S; Tanaka K; Fukumoto K; Nishiyama T; Kito S; Mizowaki T
    Med Phys; 2023 Sep; 50(9):5585-5596. PubMed ID: 36932977
    [TBL] [Abstract][Full Text] [Related]  

  • 70. Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions.
    Romeo V; Cuocolo R; Apolito R; Stanzione A; Ventimiglia A; Vitale A; Verde F; Accurso A; Amitrano M; Insabato L; Gencarelli A; Buonocore R; Argenzio MR; Cascone AM; Imbriaco M; Maurea S; Brunetti A
    Eur Radiol; 2021 Dec; 31(12):9511-9519. PubMed ID: 34018057
    [TBL] [Abstract][Full Text] [Related]  

  • 71. Deriving quantitative information from multiparametric MRI via Radiomics: Evaluation of the robustness and predictive value of radiomic features in the discrimination of low-grade versus high-grade gliomas with machine learning.
    Ubaldi L; Saponaro S; Giuliano A; Talamonti C; Retico A
    Phys Med; 2023 Mar; 107():102538. PubMed ID: 36796177
    [TBL] [Abstract][Full Text] [Related]  

  • 72. Scoring hypoechogenic areas in one parotid and one submandibular gland increases feasibility of ultrasound in primary Sjögren's syndrome.
    Mossel E; Arends S; van Nimwegen JF; Delli K; Stel AJ; Kroese FGM; Spijkervet FKL; Vissink A; Bootsma H;
    Ann Rheum Dis; 2018 Apr; 77(4):556-562. PubMed ID: 29233833
    [TBL] [Abstract][Full Text] [Related]  

  • 73. Radiomic phenotyping of the lung parenchyma in a lung cancer screening cohort.
    Haghighi B; Horng H; Noël PB; Cohen EA; Pantalone L; Vachani A; Rendle KA; Wainwright J; Saia C; Shinohara RT; Barbosa EM; Kontos D
    Sci Rep; 2023 Feb; 13(1):2040. PubMed ID: 36739358
    [TBL] [Abstract][Full Text] [Related]  

  • 74. The Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study.
    Xu Y; He X; Li Y; Pang P; Shu Z; Gong X
    J Magn Reson Imaging; 2021 Aug; 54(2):571-583. PubMed ID: 33559302
    [TBL] [Abstract][Full Text] [Related]  

  • 75. Sonolocation during submandibular sialolithotomy.
    Romero NJ; Fuson A; Kieliszak CR; Joshi AS
    Laryngoscope; 2019 Dec; 129(12):2716-2720. PubMed ID: 30801712
    [TBL] [Abstract][Full Text] [Related]  

  • 76. Optimal machine learning methods for radiomic prediction models: Clinical application for preoperative T
    Zhang MZ; Ou-Yang HQ; Jiang L; Wang CJ; Liu JF; Jin D; Ni M; Liu XG; Lang N; Yuan HS
    JOR Spine; 2021 Dec; 4(4):e1178. PubMed ID: 35005444
    [TBL] [Abstract][Full Text] [Related]  

  • 77. Prediction of MYCN Gene Amplification in Pediatric Neuroblastomas: Development of a Deep Learning-Based Tool for Automatic Tumor Segmentation and Comparative Analysis of Computed Tomography-Based Radiomics Features Harmonization.
    Yeow LY; Teh YX; Lu X; Srinivasa AC; Tan E; Tan TSE; Tang PH; Kn BP
    J Comput Assist Tomogr; 2023 Sep-Oct 01; 47(5):786-795. PubMed ID: 37707410
    [TBL] [Abstract][Full Text] [Related]  

  • 78. Deep learning-based harmonization of CT reconstruction kernels towards improved clinical task performance.
    Du D; Lv W; Lv J; Chen X; Wu H; Rahmim A; Lu L
    Eur Radiol; 2023 Apr; 33(4):2426-2438. PubMed ID: 36355196
    [TBL] [Abstract][Full Text] [Related]  

  • 79. Non-contrast Cine Cardiac Magnetic Resonance image radiomics features and machine learning algorithms for myocardial infarction detection.
    Avard E; Shiri I; Hajianfar G; Abdollahi H; Kalantari KR; Houshmand G; Kasani K; Bitarafan-Rajabi A; Deevband MR; Oveisi M; Zaidi H
    Comput Biol Med; 2022 Feb; 141():105145. PubMed ID: 34929466
    [TBL] [Abstract][Full Text] [Related]  

  • 80. Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data.
    He L; Li H; Dudley JA; Maloney TC; Brady SL; Somasundaram E; Trout AT; Dillman JR
    AJR Am J Roentgenol; 2019 Sep; 213(3):592-601. PubMed ID: 31120779
    [No Abstract]   [Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.