BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

220 related articles for article (PubMed ID: 33194609)

  • 1. A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy.
    Qiu X; Gao J; Yang J; Hu J; Hu W; Kong L; Lu JJ
    Front Oncol; 2020; 10():551420. PubMed ID: 33194609
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A machine learning-based survival prediction model of high grade glioma by integration of clinical and dose-volume histogram parameters.
    Chen H; Li C; Zheng L; Lu W; Li Y; Wei Q
    Cancer Med; 2021 Apr; 10(8):2774-2786. PubMed ID: 33760360
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy.
    Qiu X; Gao J; Yang J; Hu J; Hu W; Zhang X; Lu JJ; Kong L
    Ann Transl Med; 2022 Nov; 10(22):1199. PubMed ID: 36544672
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The Application and Comparison of Machine Learning Models for the Prediction of Breast Cancer Prognosis: Retrospective Cohort Study.
    Xiao J; Mo M; Wang Z; Zhou C; Shen J; Yuan J; He Y; Zheng Y
    JMIR Med Inform; 2022 Feb; 10(2):e33440. PubMed ID: 35179504
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study.
    Yang X; Qiu H; Wang L; Wang X
    J Med Internet Res; 2023 Oct; 25():e44417. PubMed ID: 37883174
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Progression-Free Survival Prediction in Patients with Nasopharyngeal Carcinoma after Intensity-Modulated Radiotherapy: Machine Learning vs. Traditional Statistics.
    Oei RW; Lyu Y; Ye L; Kong F; Du C; Zhai R; Xu T; Shen C; He X; Kong L; Hu C; Ying H
    J Pers Med; 2021 Aug; 11(8):. PubMed ID: 34442430
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prognosis prediction for glioblastoma multiforme patients using machine learning approaches: Development of the clinically applicable model.
    Kim Y; Kim KH; Park J; Yoon HI; Sung W
    Radiother Oncol; 2023 Jun; 183():109617. PubMed ID: 36921767
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine learning-based prediction of 1-year mortality for acute coronary syndrome
    Hadanny A; Shouval R; Wu J; Gale CP; Unger R; Zahger D; Gottlieb S; Matetzky S; Goldenberg I; Beigel R; Iakobishvili Z
    J Cardiol; 2022 Mar; 79(3):342-351. PubMed ID: 34857429
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [Application value of machine learning algorithms for predicting recurrence after resection of early-stage hepatocellular carcinoma].
    Ji GW; Wang K; Xia YX; Li XC; Wang XH
    Zhonghua Wai Ke Za Zhi; 2021 Aug; 59(8):679-685. PubMed ID: 34192861
    [No Abstract]   [Full Text] [Related]  

  • 11. Explainable deep learning-based survival prediction for non-small cell lung cancer patients undergoing radical radiotherapy.
    Astley JR; Reilly JM; Robinson S; Wild JM; Hatton MQ; Tahir BA
    Radiother Oncol; 2024 Apr; 193():110084. PubMed ID: 38244779
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Particle radiation therapy in the management of malignant glioma: Early experience at the Shanghai Proton and Heavy Ion Center.
    Kong L; Wu J; Gao J; Qiu X; Yang J; Hu J; Hu W; Mao Y; Lu JJ
    Cancer; 2020 Jun; 126(12):2802-2810. PubMed ID: 32167589
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Which model is better in predicting the survival of laryngeal squamous cell carcinoma?: Comparison of the random survival forest based on machine learning algorithms to Cox regression: analyses based on SEER database.
    Sun H; Wu S; Li S; Jiang X
    Medicine (Baltimore); 2023 Mar; 102(10):e33144. PubMed ID: 36897699
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangiocarcinoma.
    Wang D; Pan B; Huang JC; Chen Q; Cui SP; Lang R; Lyu SC
    Front Oncol; 2023; 13():1106029. PubMed ID: 37007095
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development of a machine learning model to predict early recurrence for hepatocellular carcinoma after curative resection.
    Zeng J; Zeng J; Lin K; Lin H; Wu Q; Guo P; Zhou W; Liu J
    Hepatobiliary Surg Nutr; 2022 Apr; 11(2):176-187. PubMed ID: 35464276
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Individual risk prediction: Comparing random forests with Cox proportional-hazards model by a simulation study.
    Baralou V; Kalpourtzi N; Touloumi G
    Biom J; 2023 Aug; 65(6):e2100380. PubMed ID: 36169048
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Interpretable machine learning for predicting chronic kidney disease progression risk.
    Zheng JX; Li X; Zhu J; Guan SY; Zhang SX; Wang WM
    Digit Health; 2024; 10():20552076231224225. PubMed ID: 38235416
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A comparative study of forest methods for time-to-event data: variable selection and predictive performance.
    Liu Y; Zhou S; Wei H; An S
    BMC Med Res Methodol; 2021 Sep; 21(1):193. PubMed ID: 34563138
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning models for predicting the survival of patients with chondrosarcoma based on a surveillance, epidemiology, and end results analysis.
    Yan L; Gao N; Ai F; Zhao Y; Kang Y; Chen J; Weng Y
    Front Oncol; 2022; 12():967758. PubMed ID: 36072795
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of time-to-event machine learning models in predicting oral cavity cancer prognosis.
    Adeoye J; Hui L; Koohi-Moghadam M; Tan JY; Choi SW; Thomson P
    Int J Med Inform; 2022 Jan; 157():104635. PubMed ID: 34800847
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.