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Tesi etd-02132017-114058


Tipo di tesi
Tesi di laurea specialistica
Autore
PODDA, MARCO
URN
etd-02132017-114058
Titolo
Predicting mortality in low birth-weight infants: a machine learning perspective
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Prof. Micheli, Alessio
relatore Dott. Bacciu, Davide
controrelatore Prof.ssa Bernasconi, Anna
Parole chiave
  • cross-validation
  • models
  • network
  • oxford
  • predictions
  • preprocessing
  • roc
  • vermont
  • von
Data inizio appello
03/03/2017
Consultabilità
Completa
Riassunto
Mortality predictions of low and very low birth-weight infants using logistic regression models are widely used in risk adjustment procedures for comparing different NICUs (Neonatal Intensive Care Units).
We tackled this problem from a machine learning point of view by training state-of-the-art supervised models for the task. Furthermore, we used unsupervised techniques to provide clinicians with new insights on the matter that could ultimately lead to new improvements.
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