# name
Ciencia de datos para la predicción de mortalidad hospitalaria y duración de la estancia en la UCI con MIMIC-III

# metadata.dc.description[].value
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2021, Director: Laura Igual Muñoz

# metadata.dc.description.abstract[].value
[en] The digitalization of medical records generates a huge amount of data, which opens up many opportunities for researchers in the field of data mining. Applying data science, we can bring innovation to the healthcare area.
In this work we focus on analyzing the data of critical patients from an open source database called MIMIC-III (Medical Information Mart for Intensive Care III). Specifically, we extracted various characteristics of ICU patients and used them to train machine learning and deep learning models, in order to predict the length of stay in the Intensive Care Unit and the hospital mortality. And we saw that for the two tasks mentioned above, deep learning models, such as Long Short-Term Memory, outperformed machine learning models, such as logistic regression, in terms of performance.

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Enginyeria Informàtica

# metadata.dc.title[].value
Ciencia de datos para la predicción de mortalidad hospitalaria y duración de la estancia en la UCI con MIMIC-III