Predicting breast cancer risk, recurrence and survivability Al-Quraishi, Tahsien Ali Hussein 2019, Predicting breast cancer risk, recurrence and survivability, Ph.D. thesis, School of Information Technology, Deakin University. Attached Files Name Description MIMEType Size Downloads alquraishi-predictingbreast-2020.pdf Connect to thesis application/pdf 3.29MB 5 Title Predicting breast cancer risk, recurrence and survivability Author Al-Quraishi, Tahsien Ali Hussein Institution Deakin University School School of Information Technology Faculty Faculty of Science, Engineering and Built Environment Degree type Research doctorate Degree name Ph.D. Thesis advisor Abawajy, Jemal Hussein orcid.org/0000-0001-8962-1222 Chowdhury, Morshed U. orcid.org/0000-0002-2866-4955 Date submitted 2019-10 Summary This thesis focuses on predicting breast cancer at early stages by using machine learning algorithms based on biological datasets. The accuracy of those algorithms has been improved to enable the physicians to enhance the success of treatment, thus saving lives and avoiding several further medical tests. Language eng Indigenous content off Description of original 104 p. Copyright notice ©The author Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30142351 Document type: Thesis Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Higher degree theses (Open Access) Open Access Collection   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Mon, 21 Sep 2020, 12:01:06 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 13 Abstract Views, 5 File Downloads  -  Detailed Statistics Created: Mon, 21 Sep 2020, 12:00:59 EST by Leanne Swaneveld

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.