BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

138 related articles for article (PubMed ID: 37525139)

  • 21. Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer.
    Kan Y; Dong D; Zhang Y; Jiang W; Zhao N; Han L; Fang M; Zang Y; Hu C; Tian J; Li C; Luo Y
    J Magn Reson Imaging; 2019 Jan; 49(1):304-310. PubMed ID: 30102438
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion.
    Otani S; Himoto Y; Nishio M; Fujimoto K; Moribata Y; Yakami M; Kurata Y; Hamanishi J; Ueda A; Minamiguchi S; Mandai M; Kido A
    Magn Reson Imaging; 2022 Jan; 85():161-167. PubMed ID: 34687853
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Conventional magnetic resonance imaging-based radiomic signature predicts telomerase reverse transcriptase promoter mutation status in grade II and III gliomas.
    Jiang C; Kong Z; Zhang Y; Liu S; Liu Z; Chen W; Liu P; Liu D; Wang Y; Lyu Y; Zhao D; Wang Y; You H; Feng F; Ma W
    Neuroradiology; 2020 Jul; 62(7):803-813. PubMed ID: 32239241
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Multisequence magnetic resonance imaging-based radiomics models for the prediction of microsatellite instability in endometrial cancer.
    Song XL; Luo HJ; Ren JL; Yin P; Liu Y; Niu J; Hong N
    Radiol Med; 2023 Feb; 128(2):242-251. PubMed ID: 36656410
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Establishing a predictive model for tumor mutation burden status based on CT radiomics and clinical features of non-small cell lung cancer patients.
    Yang J; Shi W; Yang Z; Yu H; Wang M; Wei Y; Wen J; Zheng W; Zhang P; Zhao W; Chen L
    Transl Lung Cancer Res; 2023 Apr; 12(4):808-823. PubMed ID: 37197623
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Combination of Proactive Molecular Risk Classifier for Endometrial cancer (ProMisE) with sonographic and demographic characteristics in preoperative prediction of recurrence or progression of endometrial cancer.
    Eriksson LSE; Nastic D; Lindqvist PG; Imboden S; Järnbert-Pettersson H; Carlson JW; Epstein E
    Ultrasound Obstet Gynecol; 2021 Sep; 58(3):457-468. PubMed ID: 33314410
    [TBL] [Abstract][Full Text] [Related]  

  • 27. DACH1 mutation frequency in endometrial cancer is associated with high tumor mutation burden.
    Riggs MJ; Lin N; Wang C; Piecoro DW; Miller RW; Hampton OA; Rao M; Ueland FR; Kolesar JM
    PLoS One; 2020; 15(12):e0244558. PubMed ID: 33378353
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Predicting myometrial invasion in endometrial cancer based on whole-uterine magnetic resonance radiomics.
    Han Y; Xu H; Ming Y; Liu Q; Huang C; Xu J; Zhang J; Li Y
    J Cancer Res Ther; 2020; 16(7):1648-1655. PubMed ID: 33565512
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 3D DCE-MRI Radiomic Analysis for Malignant Lesion Prediction in Breast Cancer Patients.
    Militello C; Rundo L; Dimarco M; Orlando A; Woitek R; D'Angelo I; Russo G; Bartolotta TV
    Acad Radiol; 2022 Jun; 29(6):830-840. PubMed ID: 34600805
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Radiomic study on preoperative multi-modal magnetic resonance images identifies IDH-mutant TERT promoter-mutant gliomas.
    Wang H; Zhang S; Xing X; Yue Q; Feng W; Chen S; Zhang J; Xie D; Chen N; Liu Y
    Cancer Med; 2023 Feb; 12(3):2524-2537. PubMed ID: 36176070
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Radiomic features from dynamic susceptibility contrast perfusion-weighted imaging improve the three-class prediction of molecular subtypes in patients with adult diffuse gliomas.
    Pei D; Guan F; Hong X; Liu Z; Wang W; Qiu Y; Duan W; Wang M; Sun C; Wang W; Wang X; Guo Y; Wang Z; Liu Z; Xing A; Guo Z; Luo L; Liu X; Cheng J; Zhang B; Zhang Z; Yan J
    Eur Radiol; 2023 May; 33(5):3455-3466. PubMed ID: 36853347
    [TBL] [Abstract][Full Text] [Related]  

  • 32. The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer.
    Qu J; Shen C; Qin J; Wang Z; Liu Z; Guo J; Zhang H; Gao P; Bei T; Wang Y; Liu H; Kamel IR; Tian J; Li H
    Eur Radiol; 2019 Feb; 29(2):906-914. PubMed ID: 30039220
    [TBL] [Abstract][Full Text] [Related]  

  • 33. IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation.
    Choi Y; Nam Y; Lee YS; Kim J; Ahn KJ; Jang J; Shin NY; Kim BS; Jeon SS
    Eur J Radiol; 2020 Jul; 128():109031. PubMed ID: 32417712
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.
    Liang M; Cai Z; Zhang H; Huang C; Meng Y; Zhao L; Li D; Ma X; Zhao X
    Acad Radiol; 2019 Nov; 26(11):1495-1504. PubMed ID: 30711405
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Preoperative prediction of muscular invasiveness of bladder cancer with radiomic features on conventional MRI and its high-order derivative maps.
    Xu X; Liu Y; Zhang X; Tian Q; Wu Y; Zhang G; Meng J; Yang Z; Lu H
    Abdom Radiol (NY); 2017 Jul; 42(7):1896-1905. PubMed ID: 28217825
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI.
    Liu C; Ding J; Spuhler K; Gao Y; Serrano Sosa M; Moriarty M; Hussain S; He X; Liang C; Huang C
    J Magn Reson Imaging; 2019 Jan; 49(1):131-140. PubMed ID: 30171822
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Identification of EMT-associated LncRNA Signature for Predicting the Prognosis of Patients with Endometrial Cancer.
    Shu W; Wang Z; Zhang W; Zhang J; Zhao R; Yu Z; Dong K; Wang H
    Comb Chem High Throughput Screen; 2023; 26(8):1488-1502. PubMed ID: 36200154
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Preliminary utilization of radiomics in differentiating uterine sarcoma from atypical leiomyoma: Comparison on diagnostic efficacy of MRI features and radiomic features.
    Xie H; Hu J; Zhang X; Ma S; Liu Y; Wang X
    Eur J Radiol; 2019 Jun; 115():39-45. PubMed ID: 31084757
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study.
    Tiwari P; Prasanna P; Wolansky L; Pinho M; Cohen M; Nayate AP; Gupta A; Singh G; Hatanpaa KJ; Sloan A; Rogers L; Madabhushi A
    AJNR Am J Neuroradiol; 2016 Dec; 37(12):2231-2236. PubMed ID: 27633806
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes.
    Arefan D; Hausler RM; Sumkin JH; Sun M; Wu S
    BMC Cancer; 2021 Apr; 21(1):370. PubMed ID: 33827490
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.