{"id":"https://openalex.org/W4414054264","doi":"https://doi.org/10.1109/taffc.2025.3606949","title":"Mitigating Symptom Heterogeneity in Multimodal Depression Estimation via Level Separation and Deviation Regression","display_name":"Mitigating Symptom Heterogeneity in Multimodal Depression Estimation via Level Separation and Deviation Regression","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W4414054264","doi":"https://doi.org/10.1109/taffc.2025.3606949"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2025.3606949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3606949","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","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/A5017225839","display_name":"Chengguang Liu","orcid":"https://orcid.org/0009-0002-4830-2430"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengguang Liu","raw_affiliation_strings":["College of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000558793","display_name":"Shanmin Wang","orcid":"https://orcid.org/0000-0002-0275-803X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanmin Wang","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404959","display_name":"Qingshan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingshan Liu","raw_affiliation_strings":["School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074592532","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0003-2802-5392"},"institutions":[{"id":"https://openalex.org/I4210109791","display_name":"Nanjing Brain Hospital","ror":"https://ror.org/01wcx2305","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210109791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["Early Intervention Department of Psychiatry, Affiliated Brain Hospital, Nanjing Medical University, Nanjing, China","Early Intervention Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Early Intervention Department of Psychiatry, Affiliated Brain Hospital, Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791"]},{"raw_affiliation_string":"Early Intervention Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100455872","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0002-7650-6345"},"institutions":[{"id":"https://openalex.org/I4210109791","display_name":"Nanjing Brain Hospital","ror":"https://ror.org/01wcx2305","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210109791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Early Intervention Department of Psychiatry, Affiliated Brain Hospital, Nanjing Medical University, Nanjing, China","Early Intervention Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Early Intervention Department of Psychiatry, Affiliated Brain Hospital, Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791"]},{"raw_affiliation_string":"Early Intervention Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5017225839"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24537605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"1","first_page":"107","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.838100016117096,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.838100016117096,"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/T13283","display_name":"Mental Health Research Topics","score":0.8122000098228455,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.7870000004768372,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/depression","display_name":"Depression (economics)","score":0.7803000211715698},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6021999716758728},{"id":"https://openalex.org/keywords/multilevel-model","display_name":"Multilevel model","score":0.5623999834060669},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5418000221252441},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5177000164985657},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.4174000024795532},{"id":"https://openalex.org/keywords/depressive-symptoms","display_name":"Depressive symptoms","score":0.39419999718666077},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.38760000467300415}],"concepts":[{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.7803000211715698},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6021999716758728},{"id":"https://openalex.org/C53059260","wikidata":"https://www.wikidata.org/wiki/Q374758","display_name":"Multilevel model","level":2,"score":0.5623999834060669},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.5070000290870667},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.46779999136924744},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45590001344680786},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4117000102996826},{"id":"https://openalex.org/C3019858935","wikidata":"https://www.wikidata.org/wiki/Q4340209","display_name":"Depressive symptoms","level":3,"score":0.39419999718666077},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3871000111103058},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C120934525","wikidata":"https://www.wikidata.org/wiki/Q849149","display_name":"Absolute deviation","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.34439998865127563},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32839998602867126},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29330000281333923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2892000079154968},{"id":"https://openalex.org/C70410870","wikidata":"https://www.wikidata.org/wiki/Q199906","display_name":"Clinical psychology","level":1,"score":0.2648000121116638},{"id":"https://openalex.org/C181243257","wikidata":"https://www.wikidata.org/wiki/Q1693522","display_name":"Sample mean and sample covariance","level":3,"score":0.26440000534057617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C51989270","wikidata":"https://www.wikidata.org/wiki/Q623738","display_name":"Relative standard deviation","level":3,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2025.3606949","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3606949","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1577400252","https://openalex.org/W1584308190","https://openalex.org/W1821071970","https://openalex.org/W1884002324","https://openalex.org/W1966268437","https://openalex.org/W1976066595","https://openalex.org/W2009088607","https://openalex.org/W2048533792","https://openalex.org/W2056403322","https://openalex.org/W2095540482","https://openalex.org/W2102505790","https://openalex.org/W2132322340","https://openalex.org/W2164104699","https://openalex.org/W2182295029","https://openalex.org/W2182998784","https://openalex.org/W2310007339","https://openalex.org/W2336589871","https://openalex.org/W2529925562","https://openalex.org/W2560565629","https://openalex.org/W2581084710","https://openalex.org/W2751214333","https://openalex.org/W2896134990","https://openalex.org/W2949676527","https://openalex.org/W2964051877","https://openalex.org/W2970055828","https://openalex.org/W2995040299","https://openalex.org/W2996751911","https://openalex.org/W3004404036","https://openalex.org/W3041635669","https://openalex.org/W3080748802","https://openalex.org/W3084346048","https://openalex.org/W3093051361","https://openalex.org/W3094259155","https://openalex.org/W3094644839","https://openalex.org/W3155791660","https://openalex.org/W3200946425","https://openalex.org/W3214493799","https://openalex.org/W4200262469","https://openalex.org/W4224917453","https://openalex.org/W4285132306","https://openalex.org/W4285176735","https://openalex.org/W4288804239","https://openalex.org/W4308160155","https://openalex.org/W4312061384","https://openalex.org/W4312729661","https://openalex.org/W4312930335","https://openalex.org/W4313443450","https://openalex.org/W4321353437","https://openalex.org/W4322774433","https://openalex.org/W4385245566","https://openalex.org/W4386424478","https://openalex.org/W4386736917","https://openalex.org/W4387010698","https://openalex.org/W4388041655","https://openalex.org/W4388833473","https://openalex.org/W4389314870","https://openalex.org/W4390331593","https://openalex.org/W4391242251","https://openalex.org/W4399205274","https://openalex.org/W4400228817","https://openalex.org/W4402776463","https://openalex.org/W4403792402","https://openalex.org/W4404473968","https://openalex.org/W4406387536","https://openalex.org/W4406903994"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W1969346022","https://openalex.org/W2034959125","https://openalex.org/W2355687852"],"abstract_inverted_index":{"Multimodal":[0,24],"Depression":[1,25,74,104],"Estimation":[2],"(MDE)":[3],"aims":[4],"to":[5,23,46,97,144,160],"infer":[6,161],"individual":[7],"depression":[8,87,108,150,154,163,191],"scores":[9],"by":[10],"analyzing":[11],"various":[12],"signals,":[13],"such":[14],"as":[15],"visual,":[16],"auditory,":[17],"and":[18,76,89,117,156,173],"language":[19],"signals":[20],"etc.":[21],"Compared":[22],"Detection":[26],"(MDD)":[27],"methods":[28],"that":[29,178],"only":[30],"provide":[31,36],"discrete":[32],"labels,":[33],"MDE":[34,64,198],"can":[35],"a":[37,72],"more":[38,165],"refined":[39],"score":[40,164],"evaluation.":[41],"However,":[42],"symptom":[43,188],"heterogeneity":[44,189],"leads":[45],"differences":[47],"in":[48,197],"external":[49],"behaviors":[50],"among":[51],"patients":[52],"with":[53,110,127],"similar":[54],"depressive":[55],"states,":[56],"which":[57,82],"limits":[58],"the":[59,102,119,135,148,153,162,169,179,185],"performance":[60],"of":[61,121,130,187],"direct":[62],"regression":[63],"methods.":[65],"To":[66],"address":[67],"this":[68],"issue,":[69],"we":[70],"propose":[71],"Combined":[73],"Level":[75],"Deviation":[77,137],"(CDLD)":[78],"method":[79,182],"for":[80],"MDE,":[81],"separates":[83],"samples":[84,126],"at":[85,205],"different":[86,128],"levels":[88,109,129],"further":[90],"analyzes":[91],"subtle":[92,149],"deviations":[93],"within":[94],"same":[95],"level":[96,155],"improve":[98],"estimation":[99,192],"performance.":[100],"Specifically,":[101],"Multilevel":[103],"Separation":[105],"module":[106,139],"constructs":[107],"inherent":[111],"commonalities":[112],"based":[113],"on":[114,133,168,190],"psychological":[115],"theories":[116],"models":[118],"ordinality":[120],"these":[122],"levels,":[123],"thereby":[124],"separating":[125],"depression.":[131],"Building":[132],"this,":[134],"Level-specific":[136],"Regression":[138],"contrasts":[140],"sample":[141],"features":[142],"relative":[143],"level-specific":[145],"anchors,":[146],"regressing":[147],"deviation.":[151],"Finally,":[152],"deviation":[157],"are":[158],"integrated":[159],"accurately.":[166],"Experiments":[167],"DAIC-WOZ,":[170],"CMDC,":[171],"SEARCH,":[172],"AVEC":[174],"2014":[175],"datasets":[176],"demonstrate":[177],"proposed":[180],"coarse-to-fine":[181],"effectively":[183],"mitigates":[184],"impact":[186],"performance,":[193],"showing":[194],"significant":[195],"advantages":[196],"tasks.":[199],"The":[200],"code":[201],"is":[202],"publicly":[203],"available":[204],"<uri":[206],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[207],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/LIU70KG/CDLD</uri>.":[208]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
