{"id":"https://openalex.org/W3144340278","doi":"https://doi.org/10.1109/slt48900.2021.9383609","title":"Cross-Demographic Portability of Deep NLP-Based Depression Models","display_name":"Cross-Demographic Portability of Deep NLP-Based Depression Models","publication_year":2021,"publication_date":"2021-01-19","ids":{"openalex":"https://openalex.org/W3144340278","doi":"https://doi.org/10.1109/slt48900.2021.9383609","mag":"3144340278"},"language":"en","primary_location":{"id":"doi:10.1109/slt48900.2021.9383609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt48900.2021.9383609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Spoken Language Technology Workshop (SLT)","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/A5060976819","display_name":"Tomek Rutowski","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106430","display_name":"Ellipsis","ror":"https://ror.org/01pmtzj45","country_code":"US","type":"other","lineage":["https://openalex.org/I4210106430"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tomek Rutowski","raw_affiliation_strings":["Ellipsis Health, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ellipsis Health, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107174154","display_name":"Elizabeth Shriberg","orcid":"https://orcid.org/0009-0004-3779-4956"},"institutions":[{"id":"https://openalex.org/I4210106430","display_name":"Ellipsis","ror":"https://ror.org/01pmtzj45","country_code":"US","type":"other","lineage":["https://openalex.org/I4210106430"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elizabeth Shriberg","raw_affiliation_strings":["Ellipsis Health, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ellipsis Health, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043581685","display_name":"Amir Harati","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106430","display_name":"Ellipsis","ror":"https://ror.org/01pmtzj45","country_code":"US","type":"other","lineage":["https://openalex.org/I4210106430"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir Harati","raw_affiliation_strings":["Ellipsis Health, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ellipsis Health, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037087707","display_name":"Yang L\u00fc","orcid":"https://orcid.org/0000-0001-9887-7078"},"institutions":[{"id":"https://openalex.org/I4210106430","display_name":"Ellipsis","ror":"https://ror.org/01pmtzj45","country_code":"US","type":"other","lineage":["https://openalex.org/I4210106430"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Lu","raw_affiliation_strings":["Ellipsis Health, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ellipsis Health, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106430"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067556320","display_name":"Ricardo Oliveira","orcid":"https://orcid.org/0000-0001-5167-1523"},"institutions":[{"id":"https://openalex.org/I4210106430","display_name":"Ellipsis","ror":"https://ror.org/01pmtzj45","country_code":"US","type":"other","lineage":["https://openalex.org/I4210106430"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ricardo Oliveira","raw_affiliation_strings":["Ellipsis Health, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ellipsis Health, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106430"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068244618","display_name":"Piotr Chlebek","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106430","display_name":"Ellipsis","ror":"https://ror.org/01pmtzj45","country_code":"US","type":"other","lineage":["https://openalex.org/I4210106430"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Piotr Chlebek","raw_affiliation_strings":["Ellipsis Health, Inc., San Francisco, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ellipsis Health, Inc., San Francisco, CA, USA","institution_ids":["https://openalex.org/I4210106430"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210106430"],"apc_list":null,"apc_paid":null,"fwci":3.2261,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.92654691,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1052","last_page":"1057"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.994700014591217,"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/T10028","display_name":"Topic Modeling","score":0.9907000064849854,"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/software-portability","display_name":"Software portability","score":0.9311214685440063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7005490064620972},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6924257278442383},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5666235089302063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5051291584968567},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.48214098811149597},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42487892508506775},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1809859573841095}],"concepts":[{"id":"https://openalex.org/C63000827","wikidata":"https://www.wikidata.org/wiki/Q3080428","display_name":"Software portability","level":2,"score":0.9311214685440063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7005490064620972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6924257278442383},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5666235089302063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5051291584968567},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.48214098811149597},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42487892508506775},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1809859573841095},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/slt48900.2021.9383609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt48900.2021.9383609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Spoken Language Technology Workshop (SLT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W121610373","https://openalex.org/W2047388850","https://openalex.org/W2099274262","https://openalex.org/W2116825089","https://openalex.org/W2153579005","https://openalex.org/W2155489249","https://openalex.org/W2163680580","https://openalex.org/W2163928333","https://openalex.org/W2171340584","https://openalex.org/W2250539671","https://openalex.org/W2252180568","https://openalex.org/W2322892874","https://openalex.org/W2399733683","https://openalex.org/W2746201090","https://openalex.org/W2751214333","https://openalex.org/W2766483729","https://openalex.org/W2767088461","https://openalex.org/W2806881496","https://openalex.org/W2889056793","https://openalex.org/W2889327511","https://openalex.org/W2894821115","https://openalex.org/W2962784628","https://openalex.org/W2962832505","https://openalex.org/W2963026768","https://openalex.org/W2963261455","https://openalex.org/W2963494889","https://openalex.org/W2963979492","https://openalex.org/W2964352358","https://openalex.org/W2973091199","https://openalex.org/W2981677410","https://openalex.org/W2982049122","https://openalex.org/W2990825125","https://openalex.org/W3025499029","https://openalex.org/W4232130578","https://openalex.org/W4294170691","https://openalex.org/W4298422451","https://openalex.org/W4299838440","https://openalex.org/W6638575559","https://openalex.org/W6674573636","https://openalex.org/W6682691769","https://openalex.org/W6691669583","https://openalex.org/W6727099177","https://openalex.org/W6742632731"],"related_works":["https://openalex.org/W107105315","https://openalex.org/W4367156293","https://openalex.org/W1584537303","https://openalex.org/W4388155270","https://openalex.org/W1872724644","https://openalex.org/W2750549761","https://openalex.org/W28826848","https://openalex.org/W2122272819","https://openalex.org/W2130894091","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"models":[2,23,35],"are":[3,146],"rapidly":[4],"gaining":[5],"interest":[6],"for":[7,113,127,140],"real-world":[8],"applications":[9,145],"in":[10,16,45,102,111,120],"behavioral":[11],"health.":[12],"An":[13],"important":[14],"gap":[15],"current":[17],"literature":[18],"is":[19,56,135],"how":[20],"well":[21],"such":[22],"generalize":[24],"over":[25,39,137],"different":[26,41],"populations.":[27],"We":[28,81],"study":[29],"Natural":[30],"Language":[31],"Processing":[32],"(NLP)":[33],"based":[34],"to":[36,58,63],"explore":[37],"portability":[38,142],"two":[40,104],"corpora":[42],"highly":[43],"mismatched":[44],"age.":[46],"The":[47],"first":[48],"and":[49],"larger":[50],"corpus":[51],"contains":[52],"younger":[53],"speakers.":[54],"It":[55],"used":[57],"train":[59],"an":[60],"NLP":[61],"model":[62,77,85],"predict":[64],"depression.":[65],"When":[66],"testing":[67],"on":[68,86],"unseen":[69],"speakers":[70],"from":[71,93],"the":[72,87,98,103,114,121,128],"same":[73],"age":[74],"distribution,":[75],"this":[76,84],"performs":[78],"at":[79],"AUC=0.82.":[80],"then":[82],"test":[83],"second":[88],"corpus,":[89],"which":[90],"comprises":[91],"seniors":[92],"a":[94],"retirement":[95],"community.":[96],"Despite":[97],"large":[99],"demographic":[100,141],"differences":[101],"corpora,":[105],"we":[106,124],"saw":[107],"only":[108],"modest":[109],"degradation":[110],"performance":[112],"senior-corpus":[115],"data,":[116],"achieving":[117],"AUC=0.76.":[118],"Interestingly,":[119],"senior":[122],"population,":[123],"find":[125],"AUC=0.81":[126],"subset":[129],"of":[130,143],"patients":[131],"whose":[132],"health":[133],"state":[134],"consistent":[136],"time.":[138],"Implications":[139],"speech-based":[144],"discussed.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
