Augustine, Marcellus George;
(2025)
Machine learning approaches to understanding tumour immunity.
Doctoral thesis (Ph.D), UCL (University College London).
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Augustine_10205358_thesis_sigs_removed.pdf Access restricted to UCL open access staff until 1 March 2027. Download (18MB) |
Abstract
[Redacted]
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Machine learning approaches to understanding tumour immunity |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| Keywords: | Machine learning, Artificial intelligence, Cancer, Drug discovery, Tumour immunology, Tumour microenvironment, Cancer initiation, Biomarker discovery, Bioinformatics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10205358 |
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