These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

104 related articles for article (PubMed ID: 38889522)

  • 1. Prognostication of colorectal cancer liver metastasis by CE-based radiomics and machine learning.
    Luo X; Deng H; Xie F; Wang L; Liang J; Zhu X; Li T; Tang X; Liang W; Xiang Z; He J
    Transl Oncol; 2024 Sep; 47():101997. PubMed ID: 38889522
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Exploring tumor heterogeneity in colorectal liver metastases by imaging: Unsupervised machine learning of preoperative CT radiomics features for prognostic stratification.
    Wang Q; Nilsson H; Xu K; Wei X; Chen D; Zhao D; Hu X; Wang A; Bai G
    Eur J Radiol; 2024 Jun; 175():111459. PubMed ID: 38636408
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Radiomics for therapy-specific head and neck squamous cell carcinoma survival prognostication (part I).
    Bernatz S; Böth I; Ackermann J; Burck I; Mahmoudi S; Lenga L; Martin SS; Scholtz JE; Koch V; Grünewald LD; Koch I; Stöver T; Wild PJ; Winkelmann R; Vogl TJ; Dos Santos DP
    BMC Med Imaging; 2023 Jun; 23(1):71. PubMed ID: 37268876
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Comprehensive Machine Learning Benchmark Study for Radiomics-Based Survival Analysis of CT Imaging Data in Patients With Hepatic Metastases of CRC.
    Stüber AT; Coors S; Schachtner B; Weber T; Rügamer D; Bender A; Mittermeier A; Öcal O; Seidensticker M; Ricke J; Bischl B; Ingrisch M
    Invest Radiol; 2023 Dec; 58(12):874-881. PubMed ID: 37504498
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting prognosis of resected hepatocellular carcinoma by radiomics analysis with random survival forest.
    Akai H; Yasaka K; Kunimatsu A; Nojima M; Kokudo T; Kokudo N; Hasegawa K; Abe O; Ohtomo K; Kiryu S
    Diagn Interv Imaging; 2018 Oct; 99(10):643-651. PubMed ID: 29910166
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomics based on machine learning algorithms could predict prognosis and postoperative chemotherapy benefits of patients with gastric cancer: a retrospective cohort study.
    Xiang Y; Hu Y; Chen C; Zhi H; Zhang Z; Lu M; Chen X; Luo Z; Chen S; Dias-Neto E; Pizzini P; Chen X; Chen X; Zhuang Y; Dong Q
    J Gastrointest Oncol; 2023 Oct; 14(5):2048-2063. PubMed ID: 37969820
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Overall Survival Prognostic Modelling of Non-small Cell Lung Cancer Patients Using Positron Emission Tomography/Computed Tomography Harmonised Radiomics Features: The Quest for the Optimal Machine Learning Algorithm.
    Amini M; Hajianfar G; Hadadi Avval A; Nazari M; Deevband MR; Oveisi M; Shiri I; Zaidi H
    Clin Oncol (R Coll Radiol); 2022 Feb; 34(2):114-127. PubMed ID: 34872823
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Efficiency of CT radiomics model in assessing the microsatellite instability of colorectal cancer liver metastasis.
    Wang Y; Ma L; Guo H; Wang X; Ye Z; Fan S; Gao B; Yin XP
    Curr Med Imaging; 2023 Aug; ():. PubMed ID: 37622558
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prognosis prediction of extremity and trunk wall soft-tissue sarcomas treated with surgical resection with radiomic analysis based on random survival forest.
    Yang Y; Ma X; Wang Y; Ding X
    Updates Surg; 2022 Feb; 74(1):355-365. PubMed ID: 34003477
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A radiomics-based model can predict recurrence-free survival of hepatocellular carcinoma after curative ablation.
    Peng W; Jiang X; Zhang W; Hu J; Zhang Y; Zhang L
    Asian J Surg; 2023 Jul; 46(7):2689-2696. PubMed ID: 36351862
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma.
    Deng PZ; Zhao BG; Huang XH; Xu TF; Chen ZJ; Wei QF; Liu XY; Guo YQ; Yuan SG; Liao WJ
    World J Gastroenterol; 2022 Aug; 28(31):4376-4389. PubMed ID: 36159012
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An MRI-based radiomics signature and clinical characteristics for survival prediction in early-stage cervical cancer.
    Zheng RR; Cai MT; Lan L; Huang XW; Yang YJ; Powell M; Lin F
    Br J Radiol; 2022 Jan; 95(1129):20210838. PubMed ID: 34797703
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Radiomic analysis for predicting prognosis of colorectal cancer from preoperative
    Lv L; Xin B; Hao Y; Yang Z; Xu J; Wang L; Wang X; Song S; Guo X
    J Transl Med; 2022 Feb; 20(1):66. PubMed ID: 35109864
    [TBL] [Abstract][Full Text] [Related]  

  • 14. MRI-Based Radiomic Signature as a Prognostic Biomarker for HER2-Positive Invasive Breast Cancer Treated with NAC.
    Li Q; Xiao Q; Li J; Duan S; Wang H; Gu Y
    Cancer Manag Res; 2020; 12():10603-10613. PubMed ID: 33149669
    [TBL] [Abstract][Full Text] [Related]  

  • 15. MRI-based random survival Forest model improves prediction of progression-free survival to induction chemotherapy plus concurrent Chemoradiotherapy in Locoregionally Advanced nasopharyngeal carcinoma.
    Pei W; Wang C; Liao H; Chen X; Wei Y; Huang X; Liang X; Bao H; Su D; Jin G
    BMC Cancer; 2022 Jul; 22(1):739. PubMed ID: 35794590
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Radiomics and machine learning analysis of liver magnetic resonance imaging for prediction and early detection of tumor response in colorectal liver metastases.
    Yoon S; Kim YJ; Jeon JS; Ahn SJ; Choi SJ
    Korean J Clin Oncol; 2024 May; 20(1):27-35. PubMed ID: 38988016
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine Learning Radiomics Liver Function Model for Prognostic Prediction After Radical Resection of Advanced Gastric Cancer: A Retrospective Study.
    Shao J; Jiang Z; Jiang H; Ye Q; Jiang Y; Zhang W; Huang Y; Shen X; Lu X; Wang X
    Ann Surg Oncol; 2024 Mar; 31(3):1749-1759. PubMed ID: 38112885
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Noninvasive prediction of perineural invasion in intrahepatic cholangiocarcinoma by clinicoradiological features and computed tomography radiomics based on interpretable machine learning: a multicenter cohort study.
    Liu Z; Luo C; Chen X; Feng Y; Feng J; Zhang R; Ouyang F; Li X; Tan Z; Deng L; Chen Y; Cai Z; Zhang X; Liu J; Liu W; Guo B; Hu Q
    Int J Surg; 2024 Feb; 110(2):1039-1051. PubMed ID: 37924497
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Development of a novel combined nomogram model integrating deep learning-pathomics, radiomics and immunoscore to predict postoperative outcome of colorectal cancer lung metastasis patients.
    Wang R; Dai W; Gong J; Huang M; Hu T; Li H; Lin K; Tan C; Hu H; Tong T; Cai G
    J Hematol Oncol; 2022 Jan; 15(1):11. PubMed ID: 35073937
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Ultrasound-Based Radiomics Analysis for Predicting Disease-Free Survival of Invasive Breast Cancer.
    Xiong L; Chen H; Tang X; Chen B; Jiang X; Liu L; Feng Y; Liu L; Li L
    Front Oncol; 2021; 11():621993. PubMed ID: 33996546
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.