Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients

@inproceedings{Lorenzoni2019ComparisonOM,
  title={Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients},
  author={Giulia Lorenzoni and Stefano Santo Sabato and Corrado Lanera and Daniele Bottigliengo and Clara Minto and Honoria Ocagli and Paola De Paolis and Dario Gregori and Sabino Iliceto and Franco Pisan{\`o}},
  booktitle={Journal of clinical medicine},
  year={2019}
}
  • Giulia Lorenzoni, Stefano Santo Sabato, +7 authors Franco Pisanò
  • Published in Journal of clinical medicine 2019
  • Medicine
  • The present study aims to compare the performance of eight Machine Learning Techniques (MLTs) in the prediction of hospitalization among patients with heart failure, using data from the Gestione Integrata dello Scompenso Cardiaco (GISC) study. The GISC project is an ongoing study that takes place in the region of Puglia, Southern Italy. Patients with a diagnosis of heart failure are enrolled in a long-term assistance program that includes the adoption of an online platform for data sharing… CONTINUE READING

    Create an AI-powered research feed to stay up to date with new papers like this posted to ArXiv

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 75 REFERENCES

    A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2018

    • R R Core Team
    • 2018
    VIEW 2 EXCERPTS
    HIGHLY INFLUENTIAL

    Applies Multiclass AdaBoost.M1, SAMME and Bagging. Available online: https://rdrr.io/cran/adabag/man/adabag-package.html (accessed on 1 May 2019)

    • E. Alfaro-Cortes, M. Gamez-Martinez, N. Garcia-Rubio, L. Adabag Guo
    • 2019
    VIEW 1 EXCERPT

    Artificial Intelligence in Cardiology.

    VIEW 1 EXCERPT

    Diabetes classification model based on boosting algorithms

    VIEW 1 EXCERPT

    Glmnet : Lasso and Elastic - Net Regularized Generalized Linear Models . R package version 2 . 0 . 5 2016

    • J. Friedman, T. Hastie, +3 authors J. Qian
    • R : A Language and Environment for Statistical Computing
    • 2018

    Statistical primer: sample size and power calculations—why, when and how?†

    VIEW 1 EXCERPT