BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

171 related articles for article (PubMed ID: 35029732)

  • 21. Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.
    Park YW; Oh J; You SC; Han K; Ahn SS; Choi YS; Chang JH; Kim SH; Lee SK
    Eur Radiol; 2019 Aug; 29(8):4068-4076. PubMed ID: 30443758
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.
    Tang Y; Yang CM; Su S; Wang WJ; Fan LP; Shu J
    BMC Cancer; 2021 Nov; 21(1):1268. PubMed ID: 34819043
    [TBL] [Abstract][Full Text] [Related]  

  • 23. 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]  

  • 24. COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients.
    Shiri I; Salimi Y; Pakbin M; Hajianfar G; Avval AH; Sanaat A; Mostafaei S; Akhavanallaf A; Saberi A; Mansouri Z; Askari D; Ghasemian M; Sharifipour E; Sandoughdaran S; Sohrabi A; Sadati E; Livani S; Iranpour P; Kolahi S; Khateri M; Bijari S; Atashzar MR; Shayesteh SP; Khosravi B; Babaei MR; Jenabi E; Hasanian M; Shahhamzeh A; Foroghi Ghomi SY; Mozafari A; Teimouri A; Movaseghi F; Ahmari A; Goharpey N; Bozorgmehr R; Shirzad-Aski H; Mortazavi R; Karimi J; Mortazavi N; Besharat S; Afsharpad M; Abdollahi H; Geramifar P; Radmard AR; Arabi H; Rezaei-Kalantari K; Oveisi M; Rahmim A; Zaidi H
    Comput Biol Med; 2022 Jun; 145():105467. PubMed ID: 35378436
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Diffusion radiomics as a diagnostic model for atypical manifestation of primary central nervous system lymphoma: development and multicenter external validation.
    Kang D; Park JE; Kim YH; Kim JH; Oh JY; Kim J; Kim Y; Kim ST; Kim HS
    Neuro Oncol; 2018 Aug; 20(9):1251-1261. PubMed ID: 29438500
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.
    Yin P; Mao N; Zhao C; Wu J; Sun C; Chen L; Hong N
    Eur Radiol; 2019 Apr; 29(4):1841-1847. PubMed ID: 30280245
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.
    Huang Y; Wei L; Hu Y; Shao N; Lin Y; He S; Shi H; Zhang X; Lin Y
    Front Oncol; 2021; 11():706733. PubMed ID: 34490107
    [TBL] [Abstract][Full Text] [Related]  

  • 28. 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]  

  • 29. FeAture Explorer (FAE): A tool for developing and comparing radiomics models.
    Song Y; Zhang J; Zhang YD; Hou Y; Yan X; Wang Y; Zhou M; Yao YF; Yang G
    PLoS One; 2020; 15(8):e0237587. PubMed ID: 32804986
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging.
    Dai H; Lu M; Huang B; Tang M; Pang T; Liao B; Cai H; Huang M; Zhou Y; Chen X; Ding H; Feng ST
    Quant Imaging Med Surg; 2021 May; 11(5):1836-1853. PubMed ID: 33936969
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.
    Shiri I; Maleki H; Hajianfar G; Abdollahi H; Ashrafinia S; Hatt M; Zaidi H; Oveisi M; Rahmim A
    Mol Imaging Biol; 2020 Aug; 22(4):1132-1148. PubMed ID: 32185618
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction.
    Shi P; Ray S; Zhu Q; Kon MA
    BMC Bioinformatics; 2011 Sep; 12():375. PubMed ID: 21939564
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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]  

  • 34. Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance.
    Gitto S; Bologna M; Corino VDA; Emili I; Albano D; Messina C; Armiraglio E; Parafioriti A; Luzzati A; Mainardi L; Sconfienza LM
    Radiol Med; 2022 May; 127(5):518-525. PubMed ID: 35320464
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes.
    Shen H; Chen L; Liu K; Zhao K; Li J; Yu L; Ye H; Zhu W
    Quant Imaging Med Surg; 2021 Jul; 11(7):2918-2932. PubMed ID: 34249623
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
    Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
    Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR.
    Sun K; Jiao Z; Zhu H; Chai W; Yan X; Fu C; Cheng JZ; Yan F; Shen D
    J Transl Med; 2021 Oct; 19(1):443. PubMed ID: 34689804
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A Radiomics Nomogram for Distinguishing Benign From Malignant Round-Like Breast Tumors.
    Wang L; Ding Y; Yang W; Wang H; Shen J; Liu W; Xu J; Wei R; Hu W; Ge Y; Zhang B; Song B
    Front Oncol; 2022; 12():677803. PubMed ID: 35558514
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Radiomics assessment of bladder cancer grade using texture features from diffusion-weighted imaging.
    Zhang X; Xu X; Tian Q; Li B; Wu Y; Yang Z; Liang Z; Liu Y; Cui G; Lu H
    J Magn Reson Imaging; 2017 Nov; 46(5):1281-1288. PubMed ID: 28199039
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Robust biomarker screening from gene expression data by stable machine learning-recursive feature elimination methods.
    Li L; Ching WK; Liu ZP
    Comput Biol Chem; 2022 Oct; 100():107747. PubMed ID: 35932551
    [TBL] [Abstract][Full Text] [Related]  

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