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 *

147 related articles for article (PubMed ID: 31157273)

  • 1. Predictive analytics with gradient boosting in clinical medicine.
    Zhang Z; Zhao Y; Canes A; Steinberg D; Lyashevska O;
    Ann Transl Med; 2019 Apr; 7(7):152. PubMed ID: 31157273
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of Maize Phenotypic Traits With Genomic and Environmental Predictors Using Gradient Boosting Frameworks.
    Westhues CC; Mahone GS; da Silva S; Thorwarth P; Schmidt M; Richter JC; Simianer H; Beissinger TM
    Front Plant Sci; 2021; 12():699589. PubMed ID: 34880880
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Nonparametric modeling of neural point processes via stochastic gradient boosting regression.
    Truccolo W; Donoghue JP
    Neural Comput; 2007 Mar; 19(3):672-705. PubMed ID: 17298229
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Boosting the discriminatory power of sparse survival models via optimization of the concordance index and stability selection.
    Mayr A; Hofner B; Schmid M
    BMC Bioinformatics; 2016 Jul; 17():288. PubMed ID: 27444890
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Estimating individual treatment effects by gradient boosting trees.
    Sugasawa S; Noma H
    Stat Med; 2019 Nov; 38(26):5146-5159. PubMed ID: 31460679
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Boosting for high-dimensional two-class prediction.
    Blagus R; Lusa L
    BMC Bioinformatics; 2015 Sep; 16():300. PubMed ID: 26390865
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Supervised Machine-learning Predictive Analytics for Prediction of Postinduction Hypotension.
    Kendale S; Kulkarni P; Rosenberg AD; Wang J
    Anesthesiology; 2018 Oct; 129(4):675-688. PubMed ID: 30074930
    [TBL] [Abstract][Full Text] [Related]  

  • 8. The effectiveness of internet-based e-learning on clinician behavior and patient outcomes: a systematic review protocol.
    Sinclair P; Kable A; Levett-Jones T
    JBI Database System Rev Implement Rep; 2015 Jan; 13(1):52-64. PubMed ID: 26447007
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention.
    Mortazavi BJ; Bucholz EM; Desai NR; Huang C; Curtis JP; Masoudi FA; Shaw RE; Negahban SN; Krumholz HM
    JAMA Netw Open; 2019 Jul; 2(7):e196835. PubMed ID: 31290991
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Efficient gradient boosting for prognostic biomarker discovery.
    Li K; Yao S; Zhang Z; Cao B; Wilson CM; Kalos D; Kuan PF; Zhu R; Wang X
    Bioinformatics; 2022 Mar; 38(6):1631-1638. PubMed ID: 34978570
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Gradient Boosting Decision Tree-Based Method for Predicting Interactions Between Target Genes and Drugs.
    Xuan P; Sun C; Zhang T; Ye Y; Shen T; Dong Y
    Front Genet; 2019; 10():459. PubMed ID: 31214240
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The gradient boosting algorithm and random boosting for genome-assisted evaluation in large data sets.
    González-Recio O; Jiménez-Montero JA; Alenda R
    J Dairy Sci; 2013 Jan; 96(1):614-24. PubMed ID: 23102953
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Prediction of Acute Kidney Injury after Liver Transplantation: Machine Learning Approaches vs. Logistic Regression Model.
    Lee HC; Yoon SB; Yang SM; Kim WH; Ryu HG; Jung CW; Suh KS; Lee KH
    J Clin Med; 2018 Nov; 7(11):. PubMed ID: 30413107
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Big Data and Predictive Analytics in Fire Risk Using Weather Data.
    Agarwal P; Tang J; Narayanan ANL; Zhuang J
    Risk Anal; 2020 Jul; 40(7):1438-1449. PubMed ID: 32339319
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.
    Dinh A; Miertschin S; Young A; Mohanty SD
    BMC Med Inform Decis Mak; 2019 Nov; 19(1):211. PubMed ID: 31694707
    [TBL] [Abstract][Full Text] [Related]  

  • 16. PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.
    Zhang Y; Yu S; Xie R; Li J; Leier A; Marquez-Lago TT; Akutsu T; Smith AI; Ge Z; Wang J; Lithgow T; Song J
    Bioinformatics; 2020 Feb; 36(3):704-712. PubMed ID: 31393553
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
    Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK
    Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Using predictive analytics and big data to optimize pharmaceutical outcomes.
    Hernandez I; Zhang Y
    Am J Health Syst Pharm; 2017 Sep; 74(18):1494-1500. PubMed ID: 28887351
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Detection of differential item functioning in Rasch models by boosting techniques.
    Schauberger G; Tutz G
    Br J Math Stat Psychol; 2016 Feb; 69(1):80-103. PubMed ID: 26189722
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 8.