Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/22447
Title: | Matrix decomposition algorithms for feature extraction |
Authors: | Pisani, Derrick |
Keywords: | Decomposition method Expert systems (Computer science) Artificial intelligence -- Medical applications Medical informatics |
Issue Date: | 2004 |
Publisher: | University of Malta. Faculty of ICT |
Citation: | Pisani, D. (2004). Matrix decomposition algorithms for feature extraction. 2nd Computer Science Annual Workshop (CSAW’04), Kalkara. 71-77. |
Abstract: | Clinical decision support software is a delicate system which, can potentially be the physician’s closest friend. The aim of such systems is to be able to cleverly recommend a list of treatment options which closely matches the patient. We envisage a system which learns from experts without ever needing to ask them for feedback, and thus one which learns from past patient encounters. The system needs to be adaptive as well as dynamic, since all patients are different even if they may exhibit very similar symptoms. This paper proposes using matrices to capture such data, and algorithms using Singular Value Decomposition to predict treatments. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/22447 |
Appears in Collections: | Scholarly Works - FacICTCS |
Files in This Item:
File | Description | Size | Format | |
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Proceedings of CSAW’04 - A9.pdf | 295.69 kB | Adobe PDF | View/Open |
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