{"id":"https://openalex.org/W7125947234","doi":"https://doi.org/10.1109/smc58881.2025.11343167","title":"A Novel Feature Selection Method Base on Enhanced-CDRIME and Multi-Classifiers for Pain Assessment","display_name":"A Novel Feature Selection Method Base on Enhanced-CDRIME and Multi-Classifiers for Pain Assessment","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125947234","doi":"https://doi.org/10.1109/smc58881.2025.11343167"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026381160","display_name":"Guodao Zhang","orcid":"https://orcid.org/0000-0002-6264-5854"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guodao Zhang","raw_affiliation_strings":["Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124064139","display_name":"Leqi Li","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leqi Li","raw_affiliation_strings":["Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124059844","display_name":"Yupeng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yupeng Li","raw_affiliation_strings":["Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124094963","display_name":"Xiaotian Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotian Pan","raw_affiliation_strings":["Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,Institute of Intelligent Media Computing,Hangzhou,China,310018","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124139559","display_name":"Sufang Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125219","display_name":"Lishui City People's Hospital","ror":"https://ror.org/028yz2737","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210125219"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sufang Yang","raw_affiliation_strings":["Lishui People&#x2019;s Hospital,LiShui,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lishui People&#x2019;s Hospital,LiShui,China","institution_ids":["https://openalex.org/I4210125219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035452689","display_name":"Jianwei Zhou","orcid":"https://orcid.org/0000-0002-1252-5387"},"institutions":[{"id":"https://openalex.org/I4210125219","display_name":"Lishui City People's Hospital","ror":"https://ror.org/028yz2737","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210125219"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"JianWei Zhou","raw_affiliation_strings":["Lishui People&#x2019;s Hospital,LiShui,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lishui People&#x2019;s Hospital,LiShui,China","institution_ids":["https://openalex.org/I4210125219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032701356","display_name":"Chuanguang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125219","display_name":"Lishui City People's Hospital","ror":"https://ror.org/028yz2737","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210125219"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanguang Wang","raw_affiliation_strings":["Lishui People&#x2019;s Hospital,LiShui,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lishui People&#x2019;s Hospital,LiShui,China","institution_ids":["https://openalex.org/I4210125219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7092","last_page":"7096"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10196","display_name":"Pain Mechanisms and Treatments","score":0.44850000739097595,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10196","display_name":"Pain Mechanisms and Treatments","score":0.44850000739097595,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.29660001397132874,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11199","display_name":"Pain Management and Opioid Use","score":0.037700001150369644,"subfield":{"id":"https://openalex.org/subfields/2703","display_name":"Anesthesiology and Pain Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6258000135421753},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6168000102043152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6086999773979187},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.489300012588501},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.42340001463890076},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4187999963760376},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4131999909877777}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6937000155448914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.659500002861023},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6258000135421753},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6168000102043152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6086999773979187},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4343000054359436},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.42340001463890076},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4187999963760376},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4131999909877777},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.365200012922287},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.30079999566078186},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.720791220664978,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1563088657","https://openalex.org/W1678356000","https://openalex.org/W1988790447","https://openalex.org/W2001619934","https://openalex.org/W2003233718","https://openalex.org/W2042264548","https://openalex.org/W2056132907","https://openalex.org/W2117063635","https://openalex.org/W2973941913","https://openalex.org/W3074222438","https://openalex.org/W3165837403","https://openalex.org/W3167274212","https://openalex.org/W3179951106","https://openalex.org/W3186962463","https://openalex.org/W4214489515","https://openalex.org/W4214821016","https://openalex.org/W4289236186","https://openalex.org/W4362706230","https://openalex.org/W4389778353","https://openalex.org/W4400762160"],"related_works":[],"abstract_inverted_index":{"Multi-source":[0],"physiological":[1,108,177],"signals":[2],"are":[3],"valuable":[4],"for":[5,20],"quantitative":[6],"pain":[7,111,136,176],"assessment,":[8],"but":[9],"their":[10],"high":[11],"dimensionality,":[12],"nonlinearity,":[13],"and":[14,27,50,70,83,101,126,163],"strong":[15],"inter-variable":[16],"correlations":[17],"present":[18],"challenges":[19],"clinical":[21],"decision-making.":[22],"To":[23],"improve":[24],"diagnostic":[25],"accuracy":[26,149],"efficiency,":[28],"we":[29],"propose":[30],"a":[31,46,51,65,72,106],"novel":[32],"feature":[33,81,99,124,155],"selection":[34,125],"framework":[35,56],"based":[36,140],"on":[37,123,141],"an":[38,146],"enhanced":[39],"Rime":[40],"optimization":[41],"algorithm":[42,62],"(b-CDRIME),":[43],"which":[44,85],"incorporates":[45],"co-adaptive":[47],"hunting":[48],"strategy":[49],"dispersed":[52],"foraging":[53],"strategy.":[54],"The":[55,129],"discretizes":[57],"the":[58,89,94,135,160,170],"original":[59],"continuous":[60],"CDRIME":[61,142],"by":[63],"introducing":[64],"V-shaped":[66],"binary":[67],"coding":[68],"strategy,":[69],"constructs":[71],"multi-objective":[73],"weighted":[74],"fitness":[75],"function":[76],"that":[77,134],"integrates":[78],"classification":[79,102,148],"accuracy,":[80],"dimension":[82],"AUC,":[84],"is":[86],"combined":[87],"with":[88,143],"dynamic":[90],"feedback":[91],"mechanism":[92],"of":[93,150,166,172],"classifier":[95],"to":[96,119],"achieve":[97],"efficient":[98],"screening":[100],"performance":[103,127,162],"optimization.":[104],"On":[105],"multi-source":[107,175],"signal":[109],"public":[110],"dataset,":[112],"this":[113,167],"paper":[114],"utilizes":[115],"10":[116],"classical":[117],"classifiers":[118],"test":[120],"our":[121],"methods":[122],"improvement.":[128],"comparative":[130],"experiments":[131],"results":[132],"show":[133],"assessment":[137],"model":[138],"constructed":[139],"XGBoost":[144],"has":[145],"average":[147],"81.6%":[151],"while":[152],"significantly":[153],"reducing":[154],"dimensionality.":[156],"These":[157],"findings":[158],"validate":[159],"good":[161],"application":[164],"potential":[165],"study":[168],"in":[169],"task":[171],"processing":[173],"high-dimensional":[174],"signals.":[178]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-29T00:00:00"}
