ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-06102021-163040


Tipo di tesi
Tesi di laurea magistrale
Autore
YOUSEFI, NILOOFAR
URN
etd-06102021-163040
Titolo
Exploring machine learning methods for predicting disease progression in colon cancer patients
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Prof. Sirbu, Alina
Parole chiave
  • pathways
  • regression
  • classification
  • cox regression
Data inizio appello
25/06/2021
Consultabilità
Completa
Riassunto
The main goal of this thesis is to attempt to find out if it is possible to predict the disease progression based on the mutation in pathways by using machine learning methods.
the first step is to understand the data set. there is 3 data set used in this thesis, from clinical features of each patient and average mutation in pathways for each patient
By using regression and classification we try to find the relationship among features and the disease's progression days. Cox regression provides information about how each feature has an effect on our target variable which is the cancer progression day.
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