| Autor: |
Carla Guerra Tort, Vanessa Aguiar Pulido, Victoria Suárez Ulloa, Francisco Docampo Boedo, José Manuel López Gestal, Javier Pereira Loureiro |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Proceedings, Vol 54, Iss 1, p 60 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2504-3900 |
| DOI: |
10.3390/proceedings2020054060 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
