{"created":"2025-01-19T01:30:52.617020+00:00","updated":"2025-01-19T10:58:27.781006+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230858","sets":["6504:11436:11444"]},"path":["11444"],"owner":"44499","recid":"230858","title":["アンサンブル学習を用いたスマートフォンログからのうつ状態判別モデル"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"d59c8a93-87b9-47e7-802c-5b96ebbae714"},"_deposit":{"id":"230858","pid":{"type":"depid","value":"230858","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"アンサンブル学習を用いたスマートフォンログからのうつ状態判別モデル","author_link":["622550","622552","622551"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"アンサンブル学習を用いたスマートフォンログからのうつ状態判別モデル"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータと人間社会","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/230858/files/IPSJ-Z85-6ZH-08.pdf","label":"IPSJ-Z85-6ZH-08.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-6ZH-08.pdf","filesize":[{"value":"355.2 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"4a1b9ee0-4164-44a4-bb84-dcd0e654f680","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"阪口, 航太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐久間, 拓人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"加藤, 昇平"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"うつ病は，精神科や心療内科での早期診断と適切な治療が必要であるが，医療機関への抵抗感から，多くの罹患者が受診に至っていない．そのためライフログからうつ状態を早期に検出し，医療機関の受診を促すシステムが研究されている．本研究では，スマートフォンログとアンケートの回答が記録されたデータセットを用いて，スマートフォンログを用いたうつ状態の判別モデルを提案する．大学生38名の14日間を解析対象とし，各1名の1日のスマートフォンログを1サンプルとしてうつ状態の有無を判別する．提案手法では復元抽出によるアンダーサンプリングしたデータ群を弱学習器ごとに学習し，アンサンブル学習により判別するモデルを提案する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"646","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"645","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230858,"links":{}}