Predicting adherence of patients with HF through machine learning techniques-Reference-Cited by-同舟云学术

Predicting adherence of patients with HF through machine learning techniques

Published:2016-09 Issue:3 Volume:3 Page:165-170
ISSN:2053-3713
Container-title:Healthcare Technology Letters
language:en
Short-container-title:Healthcare Technology Letters

Author:

Karanasiou Georgia Spiridon¹,Tripoliti Evanthia Eleftherios¹,Papadopoulos Theofilos Grigorios²,Kalatzis Fanis Georgios¹,Goletsis Yorgos³,Naka Katerina Kyriakos⁴⁵,Bechlioulis Aris⁴⁵,Errachid Abdelhamid⁶,Fotiadis Dimitrios Ioannis¹²

Affiliation:

1. Department of Biomedical Research Institute of Molecular Biology and Biotechnology FORTH GR 45110 Ioannina Greece

2. Unit of Medical Technology and Intelligent Information Systems University of Ioannina GR 45110 Ioannina Greece

3. Department of Economics University of Ioannina GR 45110 Ioannina Greece

4. Michaelidion Cardiac Center University of Ioannina GR 45110 Ioannina Greece

5. Department of Cardiology University of Ioannina GR 45110 Ioannina Greece

6. Université de Lyon, Institut de Sciences Analytiques, ISA FR 69100 Villeurbanne France

Publisher

Institution of Engineering and Technology (IET)

Subject

Health Information Management,Health Informatics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/htl.2016.0041

Reference40 articles.

1. Cowie M.R.: ‘The heart failure epidemic’ (Medicographia Les Laboratoires Servier France 2012)

2. Rehospitalization for Heart Failure

3. Electronically monitored medication adherence predicts hospitalization in heart failure patients

4. Medication Adherence in Patients Who Have Heart Failure: a Review of the Literature

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