Mathematical and Computational Models for Pain: A Systematic Review.
Objective There is no single prevailing theory of pain that explains its origin, qualities, and alleviation. Although many studies have investigated various molecular targets for pain management, few have attempted to examine the etiology or working mechanisms of pain through mathematical or computa...
| Publicado en: | Pain Medicine Vol. 22; no. 12; pp. 2806 - 2818 |
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| Autores principales: | , , |
| Formato: | algorithm research systematic review tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Dec2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154149794&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154149794 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15262375 FRX jtl: Pain Medicine issn: 15262375 maglogo: N pubinfo: dt: Dec2021 vid: 22 iid: 12 pid: 10398 pub: Oxford University Press / USA artinfo: ui: 154149794 154149794 154149794 10.1093/pm/pnab177 154149794 ppf: 2806 ppct: 12 formats: tig: atl: Mathematical and Computational Models for Pain: A Systematic Review. aug: au: Lang, Victoria Ashley Lundh, Torbjörn Ortiz-Catalan, Max affil: Center for Bionics and Pain Research , Sweden sug: subj: Pain Measurement Methods Pain Management Methods Mathematics Computing Methodologies Human Systematic Review Pain Etiology PubMed ab: Objective There is no single prevailing theory of pain that explains its origin, qualities, and alleviation. Although many studies have investigated various molecular targets for pain management, few have attempted to examine the etiology or working mechanisms of pain through mathematical or computational model development. In this systematic review, we identified and classified mathematical and computational models for characterizing pain. Methods The databases queried were Science Direct and PubMed , yielding 560 articles published prior to January 1st, 2020. After screening for inclusion of mathematical or computational models of pain, 31 articles were deemed relevant. Results Most of the reviewed articles utilized classification algorithms to categorize pain and no-pain conditions. We found the literature heavily focused on the application of existing models or machine learning algorithms to identify the presence or absence of pain, rather than to explore features of pain that may be used for diagnostics and treatment. Conclusions Although understudied, the development of mathematical models may augment the current understanding of pain by providing directions for testable hypotheses of its underlying mechanisms. Additional focus is needed on developing models that seek to understand the underlying mechanisms of pain, as this could potentially lead to major breakthroughs in its treatment. pubtype: Academic Journal doctype: algorithm research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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