A case study of muscle dysmorphia disorder diagnostics
► A set of indicators which describe a psychological profile of a person with MD and the degree of the disease was stated. ► Several models including regression models, decision tree and rule learners were calculated. ► The models enable to identify the most influential factors which can be used for...
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Veröffentlicht in: | Expert systems with applications 2013-08, Vol.40 (10), p.4226-4231 |
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creator | Sokolova, Marina V. González-Martí, Irene Contreras Jordán, Onofre Ricardo Fernández Bustos, Juan Gregorio |
description | ► A set of indicators which describe a psychological profile of a person with MD and the degree of the disease was stated. ► Several models including regression models, decision tree and rule learners were calculated. ► The models enable to identify the most influential factors which can be used for diagnostic purpose.
Muscle dysmorphia is a mental disorder which mainly affects young people and which may have physiological consequences. Though the nature of muscle dysmorphia has been studied, there is still a lack of scientific works explaining the hidden patterns and creation of models for this disorder. With this aim, using regression techniques, rule learners and decision tree classifiers, several models which can be useful for diagnosis and prevention of this disorder, has been obtained. |
doi_str_mv | 10.1016/j.eswa.2013.01.023 |
format | Article |
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Muscle dysmorphia is a mental disorder which mainly affects young people and which may have physiological consequences. Though the nature of muscle dysmorphia has been studied, there is still a lack of scientific works explaining the hidden patterns and creation of models for this disorder. With this aim, using regression techniques, rule learners and decision tree classifiers, several models which can be useful for diagnosis and prevention of this disorder, has been obtained.</description><subject>Classifiers</subject><subject>Decision tree</subject><subject>Decision trees</subject><subject>Diagnosis</subject><subject>Disorders</subject><subject>Expert systems</subject><subject>Modeling</subject><subject>Muscle dysmorphia</subject><subject>Muscles</subject><subject>Regression</subject><subject>Young people</subject><issn>0957-4174</issn><issn>1873-6793</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkDtPwzAUhS0EEqXwB5gysiRcx44dSyxVxUuqxAKz5fgBrpKm-Cag_nsSlRmme4fzHel8hFxTKChQcbstPH6bogTKCqAFlOyELGgtWS6kYqdkAaqSOaeSn5MLxC0AlQByQcQqswZ9hsPoDlkfsm5E2_rMHbDr0_4jmsxF7JPzaXrM-67HIVq8JGfBtOivfu-SvD3cv66f8s3L4_N6tcktE2LIraRVbSqjKlCMu6BYA3VTgYRGNcoFxnhj66CCYyGUgUsHFTdSiJr5ijPBluTm2LtP_efocdBdROvb1ux8P6KeVlAAJlT5f5RxxSte13NreYza1CMmH_Q-xc6kg6agZ596q2efevapgerJ5wTdHSE_7f2KPmm00e-sdzF5O2jXx7_wH3TJfR0</recordid><startdate>201308</startdate><enddate>201308</enddate><creator>Sokolova, Marina V.</creator><creator>González-Martí, Irene</creator><creator>Contreras Jordán, Onofre Ricardo</creator><creator>Fernández Bustos, Juan Gregorio</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201308</creationdate><title>A case study of muscle dysmorphia disorder diagnostics</title><author>Sokolova, Marina V. ; González-Martí, Irene ; Contreras Jordán, Onofre Ricardo ; Fernández Bustos, Juan Gregorio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c366t-c7158a5a950934df93b08b5070b9b9df334bc8f9fd3ff2f47d054a76683e54363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Classifiers</topic><topic>Decision tree</topic><topic>Decision trees</topic><topic>Diagnosis</topic><topic>Disorders</topic><topic>Expert systems</topic><topic>Modeling</topic><topic>Muscle dysmorphia</topic><topic>Muscles</topic><topic>Regression</topic><topic>Young people</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sokolova, Marina V.</creatorcontrib><creatorcontrib>González-Martí, Irene</creatorcontrib><creatorcontrib>Contreras Jordán, Onofre Ricardo</creatorcontrib><creatorcontrib>Fernández Bustos, Juan Gregorio</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Expert systems with applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sokolova, Marina V.</au><au>González-Martí, Irene</au><au>Contreras Jordán, Onofre Ricardo</au><au>Fernández Bustos, Juan Gregorio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A case study of muscle dysmorphia disorder diagnostics</atitle><jtitle>Expert systems with applications</jtitle><date>2013-08</date><risdate>2013</risdate><volume>40</volume><issue>10</issue><spage>4226</spage><epage>4231</epage><pages>4226-4231</pages><issn>0957-4174</issn><eissn>1873-6793</eissn><abstract>► A set of indicators which describe a psychological profile of a person with MD and the degree of the disease was stated. ► Several models including regression models, decision tree and rule learners were calculated. ► The models enable to identify the most influential factors which can be used for diagnostic purpose.
Muscle dysmorphia is a mental disorder which mainly affects young people and which may have physiological consequences. Though the nature of muscle dysmorphia has been studied, there is still a lack of scientific works explaining the hidden patterns and creation of models for this disorder. With this aim, using regression techniques, rule learners and decision tree classifiers, several models which can be useful for diagnosis and prevention of this disorder, has been obtained.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.eswa.2013.01.023</doi><tpages>6</tpages></addata></record> |
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subjects | Classifiers Decision tree Decision trees Diagnosis Disorders Expert systems Modeling Muscle dysmorphia Muscles Regression Young people |
title | A case study of muscle dysmorphia disorder diagnostics |
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