BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

154 related articles for article (PubMed ID: 37288469)

  • 1. Comparison of machine learning methods for predicting viral failure: a case study using electronic health record data.
    Kimaina A; Dick J; DeLong A; Chrysanthopoulou SA; Kantor R; Hogan JW
    Stat Commun Infect Dis; 2020 Sep; 12(Suppl1):20190017. PubMed ID: 37288469
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
    Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
    Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Pharmacy refill adherence compared with CD4 count changes for monitoring HIV-infected adults on antiretroviral therapy.
    Bisson GP; Gross R; Bellamy S; Chittams J; Hislop M; Regensberg L; Frank I; Maartens G; Nachega JB
    PLoS Med; 2008 May; 5(5):e109. PubMed ID: 18494555
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
    Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
    Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Study of the impact of HIV genotypic drug resistance testing on therapy efficacy.
    Van Vaerenbergh K
    Verh K Acad Geneeskd Belg; 2001; 63(5):447-73. PubMed ID: 11813503
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Optimal monitoring strategies for guiding when to switch first-line antiretroviral therapy regimens for treatment failure in adults and adolescents living with HIV in low-resource settings.
    Chang LW; Harris J; Humphreys E
    Cochrane Database Syst Rev; 2010 Apr; (4):CD008494. PubMed ID: 20393969
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A comparative study of logistic regression based machine learning techniques for prediction of early virological suppression in antiretroviral initiating HIV patients.
    Bisaso KR; Karungi SA; Kiragga A; Mukonzo JK; Castelnuovo B
    BMC Med Inform Decis Mak; 2018 Sep; 18(1):77. PubMed ID: 30180893
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, Ethiopia, 2022.
    Mamo DN; Yilma TM; Fekadie M; Sebastian Y; Bizuayehu T; Melaku MS; Walle AD
    BMC Med Inform Decis Mak; 2023 Apr; 23(1):75. PubMed ID: 37085851
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment.
    Wong A; Young AT; Liang AS; Gonzales R; Douglas VC; Hadley D
    JAMA Netw Open; 2018 Aug; 1(4):e181018. PubMed ID: 30646095
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Pharmacy refill adherence outperforms self-reported methods in predicting HIV therapy outcome in resource-limited settings.
    Sangeda RZ; Mosha F; Prosperi M; Aboud S; Vercauteren J; Camacho RJ; Lyamuya EF; Van Wijngaerden E; Vandamme AM
    BMC Public Health; 2014 Oct; 14():1035. PubMed ID: 25280535
    [TBL] [Abstract][Full Text] [Related]  

  • 11. CD4 criteria improves the sensitivity of a clinical algorithm developed to identify viral failure in HIV-positive patients on antiretroviral therapy.
    Evans DH; Fox MP; Maskew M; McNamara L; MacPhail P; Mathews C; Sanne I
    J Int AIDS Soc; 2014; 17(1):19139. PubMed ID: 25227265
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Dynamic prediction of psychological treatment outcomes: development and validation of a prediction model using routinely collected symptom data.
    Bone C; Simmonds-Buckley M; Thwaites R; Sandford D; Merzhvynska M; Rubel J; Deisenhofer AK; Lutz W; Delgadillo J
    Lancet Digit Health; 2021 Apr; 3(4):e231-e240. PubMed ID: 33766287
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting Health Material Accessibility: Development of Machine Learning Algorithms.
    Ji M; Liu Y; Hao T
    JMIR Med Inform; 2021 Sep; 9(9):e29175. PubMed ID: 34468321
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting hospitalization following psychiatric crisis care using machine learning.
    Blankers M; van der Post LFM; Dekker JJM
    BMC Med Inform Decis Mak; 2020 Dec; 20(1):332. PubMed ID: 33302948
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Biological signatures and prediction of an immunosuppressive status-persistent critical illness-among orthopedic trauma patients using machine learning techniques.
    Lei M; Han Z; Wang S; Guo C; Zhang X; Song Y; Lin F; Huang T
    Front Immunol; 2022; 13():979877. PubMed ID: 36325351
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting High Flow Nasal Cannula Failure in an Intensive Care Unit Using a Recurrent Neural Network With Transfer Learning and Input Data Perseveration: Retrospective Analysis.
    Pappy G; Aczon M; Wetzel R; Ledbetter D
    JMIR Med Inform; 2022 Mar; 10(3):e31760. PubMed ID: 35238792
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Accuracy of measures for antiretroviral adherence in people living with HIV.
    Smith R; Villanueva G; Probyn K; Sguassero Y; Ford N; Orrell C; Cohen K; Chaplin M; Leeflang MM; Hine P
    Cochrane Database Syst Rev; 2022 Jul; 7(7):CD013080. PubMed ID: 35871531
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?
    El-Galaly A; Grazal C; Kappel A; Nielsen PT; Jensen SL; Forsberg JA
    Clin Orthop Relat Res; 2020 Sep; 478(9):2088-2101. PubMed ID: 32667760
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Development of an electronic medical record based alert for risk of HIV treatment failure in a low-resource setting.
    Puttkammer N; Zeliadt S; Balan JG; Baseman J; Destiné R; Domerçant JW; France G; Hyppolite N; Pelletier V; Raphael NA; Sherr K; Yuhas K; Barnhart S
    PLoS One; 2014; 9(11):e112261. PubMed ID: 25390044
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Using electronic health records to identify candidates for human immunodeficiency virus pre-exposure prophylaxis: An application of super learning to risk prediction when the outcome is rare.
    Gruber S; Krakower D; Menchaca JT; Hsu K; Hawrusik R; Maro JC; Cocoros NM; Kruskal BA; Wilson IB; Mayer KH; Klompas M
    Stat Med; 2020 Oct; 39(23):3059-3073. PubMed ID: 32578905
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.