BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

207 related articles for article (PubMed ID: 34885164)

  • 1. Deep Learning Predicts the Malignant-Transformation-Free Survival of Oral Potentially Malignant Disorders.
    Adeoye J; Koohi-Moghadam M; Lo AWI; Tsang RK; Chow VLY; Zheng LW; Choi SW; Thomson P; Su YX
    Cancers (Basel); 2021 Dec; 13(23):. PubMed ID: 34885164
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. Development and validation of survival prediction model for gastric adenocarcinoma patients using deep learning: A SEER-based study.
    Zeng J; Li K; Cao F; Zheng Y
    Front Oncol; 2023; 13():1131859. PubMed ID: 36959782
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.
    Wang S; Shao M; Fu Y; Zhao R; Xing Y; Zhang L; Xu Y
    Sci Rep; 2024 Jun; 14(1):13232. PubMed ID: 38853169
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep learning model for predicting the survival of patients with primary gastrointestinal lymphoma based on the SEER database and a multicentre external validation cohort.
    Wang F; Chen L; Liu L; Jia Y; Li W; Wang L; Zhi J; Liu W; Li W; Li Z
    J Cancer Res Clin Oncol; 2023 Oct; 149(13):12177-12189. PubMed ID: 37428248
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.
    Jiang C; Wang K; Yan L; Yao H; Shi H; Lin R
    Cancer Med; 2023 Jun; 12(11):12413-12424. PubMed ID: 37165971
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine learning methods for accurately predicting survival and guiding treatment in stage I and II hepatocellular carcinoma.
    Li X; Bao H; Shi Y; Zhu W; Peng Z; Yan L; Chen J; Shu X
    Medicine (Baltimore); 2023 Nov; 102(45):e35892. PubMed ID: 37960763
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Predicting overall survival in chordoma patients using machine learning models: a web-app application.
    Cheng P; Xie X; Knoedler S; Mi B; Liu G
    J Orthop Surg Res; 2023 Sep; 18(1):652. PubMed ID: 37660044
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine Learning-Based Overall Survival Prediction of Elderly Patients With Multiple Myeloma From Multicentre Real-Life Data.
    Bao L; Wang YT; Zhuang JL; Liu AJ; Dong YJ; Chu B; Chen XH; Lu MQ; Shi L; Gao S; Fang LJ; Xiang QQ; Ding YH
    Front Oncol; 2022; 12():922039. PubMed ID: 35865475
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning-based relapse prediction of neuromyelitis optica spectrum disorder with anti-aquaporin-4 antibody.
    Wang L; Du L; Li Q; Li F; Wang B; Zhao Y; Meng Q; Li W; Pan J; Xia J; Wu S; Yang J; Li H; Ma J; ZhangBao J; Huang W; Chang X; Tan H; Yu J; Zhou L; Lu C; Wang M; Dong Q; Lu J; Zhao C; Quan C
    Front Neurol; 2022; 13():947974. PubMed ID: 35989911
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Deep Learning for the Prediction of the Survival of Midline Diffuse Glioma with an H3K27M Alteration.
    Huang B; Chen T; Zhang Y; Mao Q; Ju Y; Liu Y; Wang X; Li Q; Lei Y; Ren Y
    Brain Sci; 2023 Oct; 13(10):. PubMed ID: 37891850
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparison of State-of-the-Art Neural Network Survival Models with the Pooled Cohort Equations for Cardiovascular Disease Risk Prediction.
    Deng Y; Liu L; Jiang H; Peng Y; Wei Y; Zhou Z; Zhong Y; Zhao Y; Yang X; Yu J; Lu Z; Kho A; Ning H; Allen NB; Wilkins JT; Liu K; Lloyd-Jones DM; Zhao L
    BMC Med Res Methodol; 2023 Jan; 23(1):22. PubMed ID: 36694118
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma.
    Byun SS; Heo TS; Choi JM; Jeong YS; Kim YS; Lee WK; Kim C
    Sci Rep; 2021 Jan; 11(1):1242. PubMed ID: 33441830
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Comparison of MRI radiomics-based machine learning survival models in predicting prognosis of glioblastoma multiforme.
    Zhang D; Luan J; Liu B; Yang A; Lv K; Hu P; Han X; Yu H; Shmuel A; Ma G; Zhang C
    Front Med (Lausanne); 2023; 10():1271687. PubMed ID: 38098850
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 11.