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- Publisher Website: 10.1016/j.eswa.2011.01.106
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Article: A probabilistic SVM based decision system for pain diagnosis
| Title | A probabilistic SVM based decision system for pain diagnosis | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Authors | |||||||||
| Keywords | Clinical experience Clinical treatments Decision rules Expert knowledge Low-back pain | ||||||||
| Issue Date | 2011 | ||||||||
| Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa | ||||||||
| Citation | Expert Systems With Applications, 2011, v. 38 n. 8, p. 9346-9351 How to Cite? | ||||||||
| Abstract | Low back pain (LBP) affects a large proportion of the population and is the main cause of work disabilities worldwide. The mechanism of LBP remains largely unknown and many existing clinical treatment of LBP may be not effective to individual patients. Thus the diagnosis and treatment evaluation is crucial for LBP patients. Probabilistic support vector machine (PSVM) decision system is proposed in this article to deal with the diagnosis and treatment evaluation of LBP. The decision system consists of qualitative knowledge model and quantitative model. Expert knowledge and clinical experience are integrated into the design. To deal with the uncertainties in patients samples, PSVM is employed to learn the decision rules from data. The proposed decision system is applied to LBP patients and achieves better performance than the original system. © 2011 Published by Elsevier Ltd. | ||||||||
| Persistent Identifier | http://hdl.handle.net/10722/135311 | ||||||||
| ISSN | 2021 Impact Factor: 8.665 2020 SCImago Journal Rankings: 1.368 | ||||||||
| ISI Accession Number ID |
Funding Information: Authors would like to thank Dr. Xinjiang Lu, Dr. Xiaogang Duan, and Mr. Hongtao Liu for their valuable discussions. The project is partially supported by a SRG grant from City University of Hong Kong (7008057), a GRF grant from RGC of Hong Kong (GRF 712408E) and S.K. Yee Medical Foundation (207210). | ||||||||
| Grants |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Yang, J | en_US |
| dc.contributor.author | Li, HX | en_US |
| dc.contributor.author | Hu, Y | en_US |
| dc.date.accessioned | 2011-07-27T01:33:11Z | - |
| dc.date.available | 2011-07-27T01:33:11Z | - |
| dc.date.issued | 2011 | en_US |
| dc.identifier.citation | Expert Systems With Applications, 2011, v. 38 n. 8, p. 9346-9351 | en_US |
| dc.identifier.issn | 0957-4174 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/135311 | - |
| dc.description.abstract | Low back pain (LBP) affects a large proportion of the population and is the main cause of work disabilities worldwide. The mechanism of LBP remains largely unknown and many existing clinical treatment of LBP may be not effective to individual patients. Thus the diagnosis and treatment evaluation is crucial for LBP patients. Probabilistic support vector machine (PSVM) decision system is proposed in this article to deal with the diagnosis and treatment evaluation of LBP. The decision system consists of qualitative knowledge model and quantitative model. Expert knowledge and clinical experience are integrated into the design. To deal with the uncertainties in patients samples, PSVM is employed to learn the decision rules from data. The proposed decision system is applied to LBP patients and achieves better performance than the original system. © 2011 Published by Elsevier Ltd. | - |
| dc.language | eng | en_US |
| dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/eswa | - |
| dc.relation.ispartof | Expert Systems With Applications | en_US |
| dc.subject | Clinical experience | - |
| dc.subject | Clinical treatments | - |
| dc.subject | Decision rules | - |
| dc.subject | Expert knowledge | - |
| dc.subject | Low-back pain | - |
| dc.title | A probabilistic SVM based decision system for pain diagnosis | en_US |
| dc.type | Article | en_US |
| dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0957-4174&volume=38&issue=8&spage=9346&epage=9351&date=2011&atitle=A+probabilistic+SVM+based+decision+system+for+pain+diagnosis | - |
| dc.identifier.email | Hu, Y: yhud@hku.hk | en_US |
| dc.identifier.authority | Hu, Y=rp00432 | en_US |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1016/j.eswa.2011.01.106 | - |
| dc.identifier.scopus | eid_2-s2.0-79953723443 | - |
| dc.identifier.hkuros | 189055 | en_US |
| dc.identifier.volume | 38 | en_US |
| dc.identifier.issue | 8 | - |
| dc.identifier.spage | 9346 | en_US |
| dc.identifier.epage | 9351 | en_US |
| dc.identifier.isi | WOS:000290237500036 | - |
| dc.relation.project | Biomedical and electrophysiological guidance for low back pain rehabilitation and prevention | - |
| dc.identifier.citeulike | 8844943 | - |
| dc.identifier.issnl | 0957-4174 | - |