Encoding Temporal Healthcare Data for Machine Learning

Encoding Temporal Healthcare Data for Machine Learning

This thesis contains a review of previous work in the fields of encoding sequential healthcare data and predicting graft- versus- host disease, a medical condition, based on patient history using machine learning. A new encoding of such data is proposed for machine learning purposes. The proposed en...

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Bibliographic Details
Main Author: Laczik, Tamás
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Machine Learning
Temporal Data
Disease Prediction
Feature Engineering
Random Forest
Logistic Regression
Maskininlärning
tidsdata
förutsägelse av sjukdom
funktionsteknik
slumpmässig skog
logistisk regression
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299433

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299433

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