BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

174 related articles for article (PubMed ID: 30978508)

  • 1. The Promise of Machine Learning: When Will it be Delivered?
    Akbilgic O; Davis RL
    J Card Fail; 2019 Jun; 25(6):484-485. PubMed ID: 30978508
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predictive Abilities of Machine Learning Techniques May Be Limited by Dataset Characteristics: Insights From the UNOS Database.
    Miller PE; Pawar S; Vaccaro B; McCullough M; Rao P; Ghosh R; Warier P; Desai NR; Ahmad T
    J Card Fail; 2019 Jun; 25(6):479-483. PubMed ID: 30738152
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.
    Senanayake S; White N; Graves N; Healy H; Baboolal K; Kularatna S
    Int J Med Inform; 2019 Oct; 130():103957. PubMed ID: 31472443
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A machine learning-based approach to prognostic analysis of thoracic transplantations.
    Delen D; Oztekin A; Kong ZJ
    Artif Intell Med; 2010 May; 49(1):33-42. PubMed ID: 20153956
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Relative Performance of Machine Learning and Linear Regression in Predicting Quality of Life and Academic Performance of School Children in Norway: Data Analysis of a Quasi-Experimental Study.
    Froud R; Hansen SH; Ruud HK; Foss J; Ferguson L; Fredriksen PM
    J Med Internet Res; 2021 Jul; 23(7):e22021. PubMed ID: 34009128
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning for predicting cardiac events: what does the future hold?
    Patel B; Sengupta P
    Expert Rev Cardiovasc Ther; 2020 Feb; 18(2):77-84. PubMed ID: 32066289
    [No Abstract]   [Full Text] [Related]  

  • 7. Using Ensemble Machine Learning Methods for Predicting Risk of Readmission for Heart Failure.
    Mahajan SM; Ghani R
    Stud Health Technol Inform; 2019 Aug; 264():243-247. PubMed ID: 31437922
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework.
    Layeghian Javan S; Sepehri MM; Aghajani H
    J Biomed Inform; 2018 Dec; 88():70-89. PubMed ID: 30389440
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of 30-Day All-Cause Readmissions in Patients Hospitalized for Heart Failure: Comparison of Machine Learning and Other Statistical Approaches.
    Frizzell JD; Liang L; Schulte PJ; Yancy CW; Heidenreich PA; Hernandez AF; Bhatt DL; Fonarow GC; Laskey WK
    JAMA Cardiol; 2017 Feb; 2(2):204-209. PubMed ID: 27784047
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prediction of lung cancer patient survival via supervised machine learning classification techniques.
    Lynch CM; Abdollahi B; Fuqua JD; de Carlo AR; Bartholomai JA; Balgemann RN; van Berkel VH; Frieboes HB
    Int J Med Inform; 2017 Dec; 108():1-8. PubMed ID: 29132615
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine Learning for Health Services Researchers.
    Doupe P; Faghmous J; Basu S
    Value Health; 2019 Jul; 22(7):808-815. PubMed ID: 31277828
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Evaluation of three machine learning models for self-referral decision support on low back pain in primary care.
    Oude Nijeweme-d'Hollosy W; van Velsen L; Poel M; Groothuis-Oudshoorn CGM; Soer R; Hermens H
    Int J Med Inform; 2018 Feb; 110():31-41. PubMed ID: 29331253
    [TBL] [Abstract][Full Text] [Related]  

  • 13. From machine learning to deep learning: progress in machine intelligence for rational drug discovery.
    Zhang L; Tan J; Han D; Zhu H
    Drug Discov Today; 2017 Nov; 22(11):1680-1685. PubMed ID: 28881183
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment.
    Prosperi MC; Altmann A; Rosen-Zvi M; Aharoni E; Borgulya G; Bazso F; Sönnerborg A; Schülter E; Struck D; Ulivi G; Vandamme AM; Vercauteren J; Zazzi M;
    Antivir Ther; 2009; 14(3):433-42. PubMed ID: 19474477
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Machine Learning Techniques in Clinical Vision Sciences.
    Caixinha M; Nunes S
    Curr Eye Res; 2017 Jan; 42(1):1-15. PubMed ID: 27362387
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures.
    Merrill RK; Ferrandino RM; Hoffman R; Shaffer GW; Ndu A
    J Foot Ankle Surg; 2019 May; 58(3):410-416. PubMed ID: 30803914
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Clinical applications of machine learning in the diagnosis, classification, and prediction of heart failure.
    Olsen CR; Mentz RJ; Anstrom KJ; Page D; Patel PA
    Am Heart J; 2020 Nov; 229():1-17. PubMed ID: 32905873
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.
    Marucci-Wellman HR; Corns HL; Lehto MR
    Accid Anal Prev; 2017 Jan; 98():359-371. PubMed ID: 27863339
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.
    Oztekin A; Delen D; Kong ZJ
    Int J Med Inform; 2009 Dec; 78(12):e84-96. PubMed ID: 19497782
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces.
    Fergus P; Selvaraj M; Chalmers C
    Comput Biol Med; 2018 Feb; 93():7-16. PubMed ID: 29248699
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.