{"id":"https://openalex.org/W4400188920","doi":"https://doi.org/10.1109/iccae59995.2024.10569222","title":"Early Detection of Depression Using Machine Learning and Social Well-Being Survey Data","display_name":"Early Detection of Depression Using Machine Learning and Social Well-Being Survey Data","publication_year":2024,"publication_date":"2024-03-14","ids":{"openalex":"https://openalex.org/W4400188920","doi":"https://doi.org/10.1109/iccae59995.2024.10569222"},"language":"en","primary_location":{"id":"doi:10.1109/iccae59995.2024.10569222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccae59995.2024.10569222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on Computer and Automation Engineering (ICCAE)","raw_type":"proceedings-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/A5076362812","display_name":"Alex X. Wang","orcid":"https://orcid.org/0000-0002-3691-8652"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Alex X. Wang","raw_affiliation_strings":["School of Mathematics and Statistics, Victoria University of Wellington,Wellington,New Zealand"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Victoria University of Wellington,Wellington,New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102023223","display_name":"Binh Nguyen","orcid":"https://orcid.org/0000-0002-4320-2978"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Binh P. Nguyen","raw_affiliation_strings":["School of Mathematics and Statistics, Victoria University of Wellington,Wellington,New Zealand"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Victoria University of Wellington,Wellington,New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090630088","display_name":"Tom Elliott","orcid":"https://orcid.org/0000-0002-7815-6318"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Tom Elliott","raw_affiliation_strings":["Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand"],"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017938018","display_name":"James Mbinta","orcid":"https://orcid.org/0000-0003-1985-6303"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"James F. Mbinta","raw_affiliation_strings":["Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand"],"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand","institution_ids":["https://openalex.org/I41156924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027724575","display_name":"Andrew Sporle","orcid":"https://orcid.org/0000-0003-1620-473X"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Andrew Sporle","raw_affiliation_strings":["School of Social Sciences, The University of Auckland,Auckland,New Zealand"],"affiliations":[{"raw_affiliation_string":"School of Social Sciences, The University of Auckland,Auckland,New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031640821","display_name":"Colin R Simpson","orcid":"https://orcid.org/0000-0002-5194-8083"},"institutions":[{"id":"https://openalex.org/I41156924","display_name":"Victoria University of Wellington","ror":"https://ror.org/0040r6f76","country_code":"NZ","type":"education","lineage":["https://openalex.org/I41156924"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Colin R. Simpson","raw_affiliation_strings":["Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand"],"affiliations":[{"raw_affiliation_string":"Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand","institution_ids":["https://openalex.org/I41156924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5076362812"],"corresponding_institution_ids":["https://openalex.org/I41156924"],"apc_list":null,"apc_paid":null,"fwci":1.599,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.83329175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"181","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.8460000157356262,"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/T13283","display_name":"Mental Health Research Topics","score":0.8460000157356262,"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/T10168","display_name":"COVID-19 and Mental Health","score":0.8215000033378601,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical 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/T12488","display_name":"Mental Health via Writing","score":0.7749999761581421,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6271255612373352},{"id":"https://openalex.org/keywords/depression","display_name":"Depression (economics)","score":0.5207555294036865},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.40512555837631226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39015042781829834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36045563220977783}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6271255612373352},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.5207555294036865},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40512555837631226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39015042781829834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36045563220977783},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccae59995.2024.10569222","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccae59995.2024.10569222","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 16th International Conference on Computer and Automation Engineering (ICCAE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2048533792","https://openalex.org/W2404440306","https://openalex.org/W2768348081","https://openalex.org/W2949676527","https://openalex.org/W3003967326","https://openalex.org/W3021043594","https://openalex.org/W3027616527","https://openalex.org/W3047939709","https://openalex.org/W3123638009","https://openalex.org/W3127594419","https://openalex.org/W3134797990","https://openalex.org/W3153346108","https://openalex.org/W3171225668","https://openalex.org/W4214695438","https://openalex.org/W4246586105","https://openalex.org/W4319311823","https://openalex.org/W4387336228","https://openalex.org/W4388099996","https://openalex.org/W6745609711"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"This":[0],"study":[1],"aims":[2],"to":[3,41,106,200,221],"develop":[4],"an":[5,92],"explainable":[6,72,234],"machine":[7],"learning":[8],"(ML)":[9],"model":[10,74,90,123,143,150,187,210,236],"for":[11,33,63],"predicting":[12],"depression":[13,34,156,193,223],"and":[14,59,79,101,114,134,146,157,163,177,194,205,225],"risk":[15,197],"factor":[16],"explanation":[17],"of":[18,67,95,99,104,112,117,184,192,207],"this":[19],"outcome":[20],"using":[21,50],"survey":[22,30],"data.":[23],"LightGBM":[24,89,122],"was":[25,48,144],"developed":[26],"on":[27],"publicly":[28],"available":[29],"data":[31],"(n=1,382)":[32],"prediction,":[35],"while":[36],"statistical":[37],"models":[38],"were":[39,85,180],"deployed":[40],"explain":[42],"the":[43,51,54,121,137,161,168,181,190,196,208],"prediction":[44],"results.":[45],"Model":[46],"performance":[47],"assessed":[49],"areas":[52],"under":[53],"receiver":[55],"operating":[56],"characteristic":[57],"(ROC-AUC)":[58],"precision-recall":[60],"(PR-AUC)":[61],"curves":[62],"over":[64],"30":[65,138],"trials":[66,139],"5-fold":[68],"nested":[69],"cross-validation.":[70],"An":[71],"ML":[73,235],"with":[75,128],"top":[76],"important":[77],"features":[78],"SHapley":[80],"Additive":[81],"Explanations":[82],"(SHAP)":[83],"analyses":[84],"performed.":[86],"The":[87,109,186,202],"proposed":[88],"provided":[91],"average":[93,110,115],"accuracy":[94],"82.74%,":[96],"a":[97,102,152],"sensitivity":[98],"74.74%,":[100],"specificity":[103],"85.29%":[105],"detect":[107,126],"depression.":[108,129,185,201],"ROC-AUC":[111,133],"89.74%":[113],"PR-AUC":[116,135],"73.52%":[118],"confirmed":[119],"that":[120,141,172,212],"could":[124],"effectively":[125],"people":[127],"Small":[130],"variations":[131],"in":[132,217,238],"among":[136],"indicated":[140],"our":[142],"stable":[145],"robust.":[147],"Our":[148],"final":[149,209],"revealed":[151],"strong":[153],"correlation":[154],"between":[155],"COVID-19,":[158],"mainly":[159],"through":[160],"behavioural":[162],"emotional":[164],"changes":[165],"caused":[166],"by":[167],"lockdown.":[169],"We":[170],"observed":[171],"sleep":[173],"quality,":[174],"personal":[175],"affect,":[176],"demographic":[178],"characteristics":[179],"key":[182],"predictors":[183],"accurately":[188],"predicted":[189],"incidence":[191],"explained":[195],"factors":[198],"leading":[199],"accuracy,":[203],"simplicity,":[204],"interpretability":[206],"suggested":[211],"it":[213],"has":[214],"potential":[215],"application":[216],"routine":[218],"clinical":[219],"practice":[220],"assist":[222],"self-assessment":[224],"diagnosis":[226],"explanation.":[227],"These":[228],"results":[229],"may":[230],"help":[231],"guide":[232],"future":[233],"development":[237],"other":[239],"therapeutic":[240],"areas.":[241]},"counts_by_year":[{"year":2024,"cited_by_count":3}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}