BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

139 related articles for article (PubMed ID: 33680946)

  • 1. Development and Validation of a Personalized Survival Prediction Model for Uterine Adenosarcoma: A Population-Based Deep Learning Study.
    Qu W; Liu Q; Jiao X; Zhang T; Wang B; Li N; Dong T; Cui B
    Front Oncol; 2020; 10():623818. PubMed ID: 33680946
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Development and validation of a deep learning survival model for cervical adenocarcinoma patients.
    Li R; Qu W; Liu Q; Tan Y; Zhang W; Hao Y; Jiang N; Mao Z; Ye J; Jiao J; Gao Q; Cui B; Dong T
    BMC Bioinformatics; 2023 Apr; 24(1):146. PubMed ID: 37055729
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.
    Yang L; Fan X; Qin W; Xu Y; Zou B; Fan B; Wang S; Dong T; Wang L
    Cancer Med; 2022 Nov; 11(22):4246-4255. PubMed ID: 35491970
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.
    Qu Z; Wang Y; Guo D; He G; Sui C; Duan Y; Zhang X; Meng H; Lan L; Liu X
    J Gastroenterol Hepatol; 2024 May; ():. PubMed ID: 38725241
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development of a Novel Deep Learning-Based Prediction Model for the Prognosis of Operable Cervical Cancer.
    Dong T; Wang L; Li R; Liu Q; Xu Y; Wei Y; Jiao X; Li X; Zhang Y; Zhang Y; Song K; Yang X; Cui B
    Comput Math Methods Med; 2022; 2022():4364663. PubMed ID: 36471752
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Deep learning enabled prediction of 5-year survival in pediatric genitourinary rhabdomyosarcoma.
    Bhambhvani HP; Zamora A; Velaer K; Greenberg DR; Sheth KR
    Surg Oncol; 2021 Mar; 36():23-27. PubMed ID: 33276260
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Survival outcome prediction in cervical cancer: Cox models vs deep-learning model.
    Matsuo K; Purushotham S; Jiang B; Mandelbaum RS; Takiuchi T; Liu Y; Roman LD
    Am J Obstet Gynecol; 2019 Apr; 220(4):381.e1-381.e14. PubMed ID: 30582927
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep-Learning-Based Survival Prediction of Patients in Coronary Care Units.
    Yang R; Huang T; Wang Z; Huang W; Feng A; Li L; Lyu J
    Comput Math Methods Med; 2021; 2021():5745304. PubMed ID: 34976110
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Development and validation of a deep transfer learning-based multivariable survival model to predict overall survival in lung cancer.
    Zhu F; Zhong R; Li F; Li C; Din N; Sweidan H; Potluri LB; Xiong S; Li J; Cheng B; Chen Z; He J; Liang W; Pan Z
    Transl Lung Cancer Res; 2023 Mar; 12(3):471-482. PubMed ID: 37057112
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Development and Validation of a Deep Learning Model for Non-Small Cell Lung Cancer Survival.
    She Y; Jin Z; Wu J; Deng J; Zhang L; Su H; Jiang G; Liu H; Xie D; Cao N; Ren Y; Chen C
    JAMA Netw Open; 2020 Jun; 3(6):e205842. PubMed ID: 32492161
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Development and validation of machine learning models to predict survival of patients with resected stage-III NSCLC.
    Jin L; Zhao Q; Fu S; Cao F; Hou B; Ma J
    Front Oncol; 2023; 13():1092478. PubMed ID: 36994203
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Does the SORG Algorithm Predict 5-year Survival in Patients with Chondrosarcoma? An External Validation.
    Bongers MER; Thio QCBS; Karhade AV; Stor ML; Raskin KA; Lozano Calderon SA; DeLaney TF; Ferrone ML; Schwab JH
    Clin Orthop Relat Res; 2019 Oct; 477(10):2296-2303. PubMed ID: 31107338
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Risk Assessment of Pulmonary Metastasis for Cervical Cancer Patients by Ensemble Learning Models: A Large Population Based Real-World Study.
    Zhu M; Wang B; Wang T; Chen Y; He D
    Int J Gen Med; 2021; 14():8713-8723. PubMed ID: 34853529
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development and validation of a deep learning model to predict survival of patients with esophageal cancer.
    Huang C; Dai Y; Chen Q; Chen H; Lin Y; Wu J; Xu X; Chen X
    Front Oncol; 2022; 12():971190. PubMed ID: 36033454
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep-learning model for predicting the survival of rectal adenocarcinoma patients based on a surveillance, epidemiology, and end results analysis.
    Yu H; Huang T; Feng B; Lyu J
    BMC Cancer; 2022 Feb; 22(1):210. PubMed ID: 35216571
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Survival of women with Mullerian adenosarcoma: A National Cancer Data Base study.
    Seagle BL; Kanis M; Strohl AE; Shahabi S
    Gynecol Oncol; 2016 Dec; 143(3):636-641. PubMed ID: 27771166
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Significance of lymph node metastasis on survival of women with uterine adenosarcoma.
    Machida H; Nathenson MJ; Takiuchi T; Adams CL; Garcia-Sayre J; Matsuo K
    Gynecol Oncol; 2017 Mar; 144(3):524-530. PubMed ID: 28109626
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.