Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/111210
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Full metadata record
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dc.contributor.author | Banjar, H. | - |
dc.contributor.author | Adelson, D. | - |
dc.contributor.author | Brown, F. | - |
dc.contributor.author | Leclercq, T. | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Health Informatics - An International Journal, 2017; 6(2):1-21 | - |
dc.identifier.issn | 2319-3190 | - |
dc.identifier.issn | 2319-2046 | - |
dc.identifier.uri | http://hdl.handle.net/2440/111210 | - |
dc.description.abstract | Treatment management in cancer patients is largely based on the use of a standardized set of predictive and prognostic factors. The former are used to evaluate specific clinical interventions, and they can be useful for selecting treatments because they directly predict the response to a treatment. The latter are used to evaluate a patient’s overall outcomes, and can be used to identify the risks or recurrence of a disease. Current intelligent systems can be a solution for transferring advancements in molecular biology into practice, especially for predicting the molecular response to molecular targeted therapy and the prognosis of risk groups in cancer medicine. This framework primarily focuses on the importance of integrating domain knowledge in predictive and prognostic models for personalized treatment. Our personalized medicine support system provides the needed support in complex decisions and can be incorporated into a treatment guide for selecting molecular targeted therapies. | - |
dc.description.statementofresponsibility | Haneen Banjar, David Adelson, Fred Brown, and Tamara Leclercq | - |
dc.language.iso | en | - |
dc.publisher | AIRCC Publishing Corporation | - |
dc.rights | Health Informatics - An International Journal, 2017; 6(2):1-21AIRCC Journal papers published under the Creative Commons Attribution (CC BY) license. | - |
dc.source.uri | http://airccse.org/journal/hiij/index.html | - |
dc.subject | Personalized medicine support system; molecular targeted therapy; predict molecular response; risk assessment; cancer treatment | - |
dc.title | Personalized medicine support system : resolving conflict in allocation to risk groups and predicting patient molecular response to targeted therapy | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.5121/hiij.2017.6201 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Adelson, D. [0000-0003-2404-5636] | - |
dc.identifier.orcid | Brown, F. [0000-0001-6171-8786] | - |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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File | Description | Size | Format | |
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hdl_111210.pdf | Published version | 770.16 kB | Adobe PDF | View/Open |
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