Mining of patient data: towards better treatment strategies for depression
dc.contributor.author | Hadzic, Maja | |
dc.contributor.author | Hadzic, Fedja | |
dc.contributor.author | Dillon, Tharam S. | |
dc.date.accessioned | 2017-01-30T12:15:35Z | |
dc.date.available | 2017-01-30T12:15:35Z | |
dc.date.created | 2011-03-20T20:01:51Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Hadzic, Maja and Hadzic, Fedja and Dillon, Tharam S. 2010. Mining of patient data: towards better treatment strategies for depression. International Journal of Functional Informatics and Personalised Medicine. 3 (2): pp. 122-143. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/19747 | |
dc.identifier.doi | 10.1504/IJFIPM.2010.037150 | |
dc.description.abstract |
An intelligent system based on data-mining technologies that can be used to assist in the prevention and treatment of depression is described. The system integrates three different kinds of patient data as well as the data describing mental health of therapists and their interaction with the patients. The system allows for the different data to be analysed in a conjoint manner using both traditional data-mining techniques and tree-mining techniques. Interesting patterns can emerge in this way to explain various processes and dynamics involved in the onset, treatment and management of depression, and help practitioners develop better prevention and treatment strategies. | |
dc.publisher | Inderscience | |
dc.subject | data analysis | |
dc.subject | data mining | |
dc.subject | XML mining | |
dc.subject | personalised treatment | |
dc.subject | mental health | |
dc.subject | depression treatment | |
dc.subject | therapists | |
dc.subject | tree mining | |
dc.subject | patient data | |
dc.subject | personalised care | |
dc.subject | depression prevention | |
dc.title | Mining of patient data: towards better treatment strategies for depression | |
dc.type | Journal Article | |
dcterms.source.volume | 3 | |
dcterms.source.number | 2 | |
dcterms.source.startPage | 122 | |
dcterms.source.endPage | 143 | |
dcterms.source.issn | 17562112 | |
dcterms.source.title | International Journal of Functional Informatics and Personalised Medicine | |
curtin.note |
Copyright © 2010 Inderscience | |
curtin.department | Digital Ecosystems and Business Intelligence Institute (DEBII) | |
curtin.accessStatus | Open access |