The Application of Computational Statistics, Data Science and Machine Learning in the Assessment of Comorbidity and Cancer Survival

Zucker, Kieran ORCID: 0000-0003-4385-3153 (2021) The Application of Computational Statistics, Data Science and Machine Learning in the Assessment of Comorbidity and Cancer Survival. PhD thesis, University of Leeds.

Metadata

Supervisors: Hall, Geoff and Glaser, Adam and Baxter, Paul
Keywords: Comorbidity, cancer, oncology, survival, machine learning, data science, statistical computing, random forests, competing risks
Awarding institution: University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds)
Identification Number/EthosID: uk.bl.ethos.837115
Depositing User: Dr Kieran Zucker
Date Deposited: 13 Sep 2021 13:56
Last Modified: 11 Oct 2023 09:53

Download

Final eThesis - complete (pdf)

Filename: K Zucker Final Thesis.pdf

Licence: Creative Commons Licence
This work is licensed under a Creative Commons Attribution NonCommercial ShareAlike 4.0 International License

CLICK TO DOWNLOAD [img]

Export

Statistics


You do not need to contact us to get a copy of this thesis. Please use the 'Download' link(s) above to get a copy.
You can contact us about this thesis. If you need to make a general enquiry, please see the Contact us page.

CORE (COnnecting REpositories)