Thesis etd-06102021-163040 |
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Thesis type
Tesi di laurea magistrale
Author
YOUSEFI, NILOOFAR
URN
etd-06102021-163040
Thesis title
Exploring machine learning methods for predicting disease progression in colon cancer patients
Department
INFORMATICA
Course of study
DATA SCIENCE AND BUSINESS INFORMATICS
Supervisors
relatore Prof. Sirbu, Alina
Keywords
- classification
- cox regression
- pathways
- regression
Graduation session start date
25/06/2021
Availability
Full
Summary
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.
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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