BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

111 related articles for article (PubMed ID: 38734580)

  • 21. Dual-modal radiomics for predicting cervical lymph node metastasis in papillary thyroid carcinoma.
    Ren Y; Lu S; Zhang D; Wang X; Agyekum EA; Zhang J; Zhang Q; Xu F; Zhang G; Chen Y; Shen X; Zhang X; Wu T; Hu H; Shan X; Wang J; Qian X
    J Xray Sci Technol; 2023; 31(6):1263-1280. PubMed ID: 37599557
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study.
    Liu Y; Sun BJ; Zhang C; Li B; Yu XX; Du Y
    World J Gastroenterol; 2024 Apr; 30(16):2233-2248. PubMed ID: 38690027
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer.
    Zhou Y; Su GY; Hu H; Ge YQ; Si Y; Shen MP; Xu XQ; Wu FY
    Eur Radiol; 2020 Nov; 30(11):6251-6262. PubMed ID: 32500193
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Preoperative prediction of lymphovascular invasion in patients with T1 breast invasive ductal carcinoma based on radiomics nomogram using grayscale ultrasound.
    Xu ML; Zeng SE; Li F; Cui XW; Liu GF
    Front Oncol; 2022; 12():1071677. PubMed ID: 36568215
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Machine learning model based on enhanced CT radiomics for the preoperative prediction of lymphovascular invasion in esophageal squamous cell carcinoma.
    Wang Y; Bai G; Huang M; Chen W
    Front Oncol; 2024; 14():1308317. PubMed ID: 38549935
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma.
    Li Y; Yu M; Wang G; Yang L; Ma C; Wang M; Yue M; Cong M; Ren J; Shi G
    Front Oncol; 2021; 11():644165. PubMed ID: 34055613
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Radiomics Analysis of Iodine-Based Material Decomposition Images With Dual-Energy Computed Tomography Imaging for Preoperatively Predicting Microsatellite Instability Status in Colorectal Cancer.
    Wu J; Zhang Q; Zhao Y; Liu Y; Chen A; Li X; Wu T; Li J; Guo Y; Liu A
    Front Oncol; 2019; 9():1250. PubMed ID: 31824843
    [No Abstract]   [Full Text] [Related]  

  • 28. A clinical-radiomics model incorporating T2-weighted and diffusion-weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer.
    Zhang K; Ren Y; Xu S; Lu W; Xie S; Qu J; Wang X; Shen B; Pang P; Cai X; Sun J
    Med Phys; 2021 Sep; 48(9):4872-4882. PubMed ID: 34042185
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Using quantitative parameters derived from pretreatment dual-energy computed tomography to predict histopathologic features in head and neck squamous cell carcinoma.
    Shen H; Huang Y; Yuan X; Liu D; Tu C; Wang Y; Li X; Wang X; Chen Q; Zhang J
    Quant Imaging Med Surg; 2022 Feb; 12(2):1243-1256. PubMed ID: 35111620
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Risk factors of lymph node metastasis or lymphovascular invasion for early gastric cancer: a practical and effective predictive model based on international multicenter data.
    Lin JX; Wang ZK; Wang W; Desiderio J; Xie JW; Wang JB; Lu J; Chen QY; Cao LL; Lin M; Tu RH; Zheng CH; Li P; Parisi A; Zhou ZW; Huang CM
    BMC Cancer; 2019 Nov; 19(1):1048. PubMed ID: 31694573
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma.
    Wang N; Bing X; Li Y; Yao J; Dai Z; Yu D; Ouyang A
    Medicine (Baltimore); 2024 Mar; 103(10):e37288. PubMed ID: 38457546
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Dual-Energy CT Deep Learning Radiomics to Predict Macrotrabecular-Massive Hepatocellular Carcinoma.
    Li M; Fan Y; You H; Li C; Luo M; Zhou J; Li A; Zhang L; Yu X; Deng W; Zhou J; Zhang D; Zhang Z; Chen H; Xiao Y; Huang B; Wang J
    Radiology; 2023 Aug; 308(2):e230255. PubMed ID: 37606573
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Preoperative Prediction of Perineural Invasion in Oesophageal Squamous Cell Carcinoma Based on CT Radiomics Nomogram: A Multicenter Study.
    Zhou H; Zhou J; Qin C; Tian Q; Zhou S; Qin Y; Wu Y; Shi J; Feng F
    Acad Radiol; 2024 Apr; 31(4):1355-1366. PubMed ID: 37949700
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma.
    An C; Li D; Li S; Li W; Tong T; Liu L; Jiang D; Jiang L; Ruan G; Hai N; Fu Y; Wang K; Zhuo S; Tian J
    Eur J Nucl Med Mol Imaging; 2022 Mar; 49(4):1187-1199. PubMed ID: 34651229
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Spectral CT-based nomogram for preoperative prediction of perineural invasion in locally advanced gastric cancer: a prospective study.
    Li J; Xu S; Wang Y; Fang M; Ma F; Xu C; Li H
    Eur Radiol; 2023 Jul; 33(7):5172-5183. PubMed ID: 36826503
    [TBL] [Abstract][Full Text] [Related]  

  • 36. The Value of Dual-Energy Computed Tomography-Based Radiomics in the Evaluation of Interstitial Fibers of Clear Cell Renal Carcinoma.
    Bing X; Wang N; Li Y; Sun H; Yao J; Li R; Li Z; Ouyang A
    Technol Cancer Res Treat; 2024; 23():15330338241235554. PubMed ID: 38404055
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Leveraging multimodal MRI-based radiomics analysis with diverse machine learning models to evaluate lymphovascular invasion in clinically node-negative breast cancer.
    Jiang Y; Zeng Y; Zuo Z; Yang X; Liu H; Zhou Y; Fan X
    Heliyon; 2024 Jan; 10(1):e23916. PubMed ID: 38192872
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses.
    Mahmoudi S; Gruenewald LD; Eichler K; Althoff FC; Martin SS; Bernatz S; Booz C; Yel I; Kinzler MN; Ziegengeist NS; Torgashov K; Mohammed H; Geyer T; Scholtz JE; Hammerstingl RM; Weber C; Hardt SE; Sommer CM; Gruber-Rouh T; Leistner DM; Vogl TJ; Koch V
    Acad Radiol; 2023 Dec; 30(12):3010-3021. PubMed ID: 37105804
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Characterization of Benign and Malignant Pancreatic Lesions with DECT Quantitative Metrics and Radiomics.
    Ebrahimian S; Singh R; Netaji A; Madhusudhan KS; Homayounieh F; Primak A; Lades F; Saini S; Kalra MK; Sharma S
    Acad Radiol; 2022 May; 29(5):705-713. PubMed ID: 34412944
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Preoperative Prediction of Perineural Invasion and Prognosis in Gastric Cancer Based on Machine Learning through a Radiomics-Clinicopathological Nomogram.
    Jia H; Li R; Liu Y; Zhan T; Li Y; Zhang J
    Cancers (Basel); 2024 Jan; 16(3):. PubMed ID: 38339364
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.