{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00208127","sets":["1164:4179:10245:10424"]},"path":["10424"],"owner":"44499","recid":"208127","title":["診療録解析のための文のセグメント分割と意味ラベル付与"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-11-25"},"_buckets":{"deposit":"8116b488-2f25-437d-bd3b-a0c5fd0d15bf"},"_deposit":{"id":"208127","pid":{"type":"depid","value":"208127","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"診療録解析のための文のセグメント分割と意味ラベル付与","author_link":["520818","520820","520821","520819","520822"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"診療録解析のための文のセグメント分割と意味ラベル付与"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"文・セグメント","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2020-11-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京都立大学／理化学研究所革新知能統合研究センター"},{"subitem_text_value":"北見工業大学／理化学研究所革新知能統合研究センター"},{"subitem_text_value":"東京都立大学"},{"subitem_text_value":"国立病院機構"},{"subitem_text_value":"理化学研究所革新知能統合研究センター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Tokyo Metropolitan University / RIKEN AIP","subitem_text_language":"en"},{"subitem_text_value":"Kitami Institute of Technology / RIKEN AIP","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Metropolitan University","subitem_text_language":"en"},{"subitem_text_value":"National Hospital Organization","subitem_text_language":"en"},{"subitem_text_value":"RIKEN AIP","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/208127/files/IPSJ-NL20246017.pdf","label":"IPSJ-NL20246017.pdf"},"date":[{"dateType":"Available","dateValue":"2022-11-25"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL20246017.pdf","filesize":[{"value":"2.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"bf2e0171-7959-47e8-89ac-9526dcbf325e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"安道, 健一郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"奥村, 貴史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小町, 守"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"堀口, 裕正"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松本, 裕治"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10115061","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8779","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，医療の現場において生成される各種情報を研究活用するための情報基盤整備が進められてきた．そのなかでも，電子カルテに含まれる各種テキスト情報は，患者情報の中心であるため効率的かつ高精度な解析が必要である．そのため，多様な医療用自然言語処理研究が進められているが，多くの研究は主に文単位で行われてきた．しかし，文が医療文書の処理に際しての効率的な処理単位であるかは必ずしも自明ではない．そこで本研究では，効率的な電子カルテの処理に向けて，記載内容を意味単位で捉えるために文をさらに分割するセグメントを定義し，その単位での意味的解析に試行的に取り組んだ．まず，医療文書で用いられる意味的な最小単位に合致するセグメントを定義し，ダミーカルテを対象にセグメント境界をアノテーションした．その上で，各セグメントに対して内容に即した 10 種類の意味ラベルを付与した．さらに，それらを自動分類するようなモデルを構築し，セグメント分割では F1 値 0.85，意味ラベル付与では平均 F1 値 0.66 で分類されることを確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"9","bibliographic_titles":[{"bibliographic_title":"研究報告自然言語処理（NL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-11-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"17","bibliographicVolumeNumber":"2020-NL-246"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T18:55:01.761116+00:00","created":"2025-01-19T01:09:42.737024+00:00","id":208127}