{"id":"https://openalex.org/W4396594859","doi":"https://doi.org/10.1109/access.2024.3396138","title":"Feature Distribution-Based Medical Data Augmentation: Enhancing Mood Disorder Classification","display_name":"Feature Distribution-Based Medical Data Augmentation: Enhancing Mood Disorder Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396594859","doi":"https://doi.org/10.1109/access.2024.3396138"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3396138","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3396138","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10517591.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10517591.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058879816","display_name":"Joo Hun Yoo","orcid":"https://orcid.org/0000-0003-0261-6127"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joo Hun Yoo","raw_affiliation_strings":["Department of Artificial Intelligence, Sungkyunkwan University, Suwon-si, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-0261-6127","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Sungkyunkwan University, Suwon-si, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035475786","display_name":"Ji Hyun An","orcid":"https://orcid.org/0000-0002-1628-9617"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ji Hyun An","raw_affiliation_strings":["Department of Psychiatry, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Psychiatry, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011292784","display_name":"Tai\u2010Myoung Chung","orcid":"https://orcid.org/0000-0002-7687-8114"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Tai-Myoung Chung","raw_affiliation_strings":["Department of Computer Science and Engineering, Sungkyunkwan University, Suwon-si, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-7687-8114","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sungkyunkwan University, Suwon-si, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I848706"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5972,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.71364172,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"12","issue":null,"first_page":"127782","last_page":"127791"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7387590408325195},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6649734377861023},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.596684455871582},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5819642543792725},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5697563290596008},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5026040077209473},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47290313243865967},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4669908881187439},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3878454267978668},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.34031301736831665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7387590408325195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6649734377861023},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.596684455871582},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5819642543792725},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5697563290596008},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5026040077209473},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47290313243865967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4669908881187439},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3878454267978668},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34031301736831665},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3396138","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3396138","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10517591.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8479e5104d4b48e9be00d302a6072f27","is_oa":true,"landing_page_url":"https://doaj.org/article/8479e5104d4b48e9be00d302a6072f27","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 127782-127791 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3396138","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3396138","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10517591.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396594859.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2014435820","https://openalex.org/W2079210585","https://openalex.org/W2148143831","https://openalex.org/W2305246427","https://openalex.org/W2561981131","https://openalex.org/W2625625371","https://openalex.org/W2714226533","https://openalex.org/W2794022343","https://openalex.org/W2884065486","https://openalex.org/W2903777941","https://openalex.org/W2968485670","https://openalex.org/W2989219518","https://openalex.org/W3027535445","https://openalex.org/W3029036868","https://openalex.org/W3104523752","https://openalex.org/W3110009138","https://openalex.org/W3112787034","https://openalex.org/W3120574460","https://openalex.org/W3135347465","https://openalex.org/W3135420375","https://openalex.org/W3136660290","https://openalex.org/W4205164650","https://openalex.org/W4220686594","https://openalex.org/W4385463011","https://openalex.org/W4391099818"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W4405887298"],"abstract_inverted_index":{"Classification":[0],"models":[1],"using":[2,162],"deep":[3,136],"or":[4,233],"machine":[5],"learning":[6,137],"algorithms":[7],"require":[8],"a":[9,54,121,143],"sufficient":[10],"and":[11,69,107,125,197,222],"balanced":[12],"training":[13,45,154],"dataset":[14,97],"to":[15,25,43,64,81,102,150,165,218],"improve":[16,223],"performance.":[17],"Still,":[18],"they":[19],"suffer":[20],"from":[21],"data":[22,26,34,46,57,67,164,169,229],"collection":[23],"due":[24],"privacy":[27],"issues.":[28,72],"In":[29],"medical":[30,56,228],"research,":[31],"where":[32],"most":[33],"variables":[35],"are":[36,231],"sensitive":[37],"information,":[38],"it":[39,114],"is":[40,80,129,140],"more":[41],"challenging":[42],"collect":[44],"for":[47,146],"model":[48,138,220],"performance":[49,177,225],"improvement.":[50],"This":[51],"study":[52],"presents":[53],"new":[55],"augmentation":[58,170],"algorithm":[59,79,93,214],"consisting":[60],"of":[61,76,86,185,194,204],"four":[62],"steps":[63],"solve":[65],"the":[66,77,83,87,104,109,116,147,152,167,173,175,182,191,200,227],"shortage":[68],"class":[70,90],"imbalance":[71],"The":[73,92,135],"main":[74],"idea":[75],"proposed":[78,168],"reflect":[82],"core":[84],"characteristic":[85],"original":[88,96],"data\u2019s":[89],"label.":[91],"receives":[94],"an":[95,99],"as":[98],"input":[100],"value":[101],"extract":[103],"feature":[105,118,127,133],"vector":[106,119,128,145],"trains":[108],"individual":[110],"autoencoder":[111],"model.":[112],"Then":[113],"verifies":[115],"augmented":[117,153],"through":[120],"distributional":[122],"equality":[123],"check,":[124],"each":[126],"concatenated":[130,144],"into":[131],"one":[132],"vector.":[134],"inference":[139],"applied":[141,217],"on":[142,226],"second":[148],"verification,":[149],"finalize":[151],"dataset.":[155],"Our":[156],"team":[157],"performed":[158],"mood":[159],"disorder":[160],"classification":[161,176,184,193,202,224],"patient":[163],"prove":[166],"algorithm.":[171],"With":[172],"method,":[174],"improved":[178],"by":[179,237],"0.059":[180],"in":[181,190,199,235],"severity":[183,192],"major":[186],"depressive":[187],"disorder,":[188,196],"0.041":[189],"anxiety":[195],"0.073":[198],"subtype":[201],"task":[203],"bipolar":[205],"disorder.":[206],"Through":[207],"this":[208],"study,":[209],"we":[210],"proved":[211],"that":[212,230],"our":[213],"can":[215],"be":[216],"minimize":[219],"bias":[221],"unbalanced":[232],"insufficient":[234],"number":[236],"class.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}