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Electronic Health Records Exploitation Using Artificial Intelligence Techniques

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PereiraLoureiro_Javier_2020_Electronic_Health_Records_Exploitation_Using_Artificial_Intelligence_Techniques.pdf (155.4Kb)
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http://hdl.handle.net/2183/27154
Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España
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Title
Electronic Health Records Exploitation Using Artificial Intelligence Techniques
Author(s)
Guerra Tort, Carla
Aguiar-Pulido, Vanessa
Suárez-Ulloa, Victoria
Docampo Boedo, Francisco
López Gestal, José Manuel
Pereira-Loureiro, Javier
Date
2020-09-09
Citation
Guerra Tort C, Aguiar Pulido V, Suárez Ulloa V, Docampo Boedo F, López Gestal JM, Pereira Loureiro J. Electronic Health Records Exploitation Using Artificial Intelligence Techniques. Proceedings. 2020; 54(1):60-62
Abstract
[Abstract] The exploitation of electronic health records (EHRs) has multiple utilities, from predictive tasks and clinical decision support to pattern recognition. Artificial Intelligence (AI) allows to extract knowledge from EHR data in a practical way. In this study, we aim to construct a Machine Learning model from EHR data to make predictions about patients. Specifically, we will focus our analysis on patients suffering from respiratory problems. Then, we will try to predict whether those patients will have a relapse in less than 6, 12 or 18 months. The main objective is to identify the characteristics that seem to increase the relapse risk. At the same time, we propose an exploratory analysis in search of hidden patterns among data. These patterns will help us to classify patients according to their specific conditions for some clinical variables.
Keywords
Electronic health record (EHR)
Artificial Intelligence (AI)
Relapse
Respiratory diseases
 
Editor version
https://doi.org/10.3390/proceedings2020054060
Rights
Atribución 3.0 España
ISSN
2504-3900

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