{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00213079","sets":["6164:6165:6640:10712"]},"path":["10712"],"owner":"44499","recid":"213079","title":["機械学習を用いた診療録の様式分類におけるアルゴリズムの一検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-06-23"},"_buckets":{"deposit":"c3f81a96-efce-4cb2-8828-e468c2ca775f"},"_deposit":{"id":"213079","pid":{"type":"depid","value":"213079","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習を用いた診療録の様式分類におけるアルゴリズムの一検討","author_link":["544589","544588","544587"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いた診療録の様式分類におけるアルゴリズムの一検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"AI","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2021-06-23","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"公益財団法人放射線影響研究所情報技術部"},{"subitem_text_value":"公益財団法人放射線影響研究所臨床研究部"},{"subitem_text_value":"公益財団法人放射線影響研究所主席研究員"}]},"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/213079/files/IPSJ-DICOMO2021181.pdf","label":"IPSJ-DICOMO2021181.pdf"},"date":[{"dateType":"Available","dateValue":"2023-06-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2021181.pdf","filesize":[{"value":"919.8 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"2107b3e7-ab3f-4954-a9b1-fd960aa649c8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小野, 悟"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大石, 和佳"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Eric, Grant"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"放射線影響研究所では,原爆被爆者およびその二世の方々の多大な協力を賜りながら,過去 70 年以上に亘り疫学的,分子生物学的研究を継続している.その過程において,これら研究協力者の臨床的情報を体系的な記録として保管するために診療録が作成されている.診療録を構成する情報の一部は紙媒体のみでしか保存されていないため,経年劣化による情報の滅失が懸念されており,構成する各様式等の光学スキャン方式を用いた電子化を検討している.しかしながら,これらの方式では読み取られた情報は画像情報として保存されるため,適切な分類や検索のためのメタデータの付加が望ましい.そこで,パイロットスタディとして保有する診療録の一部を光学スキャン方式によって画像化し,それらの様式に対して機械学習を用いた分類を試みた.本稿ではこの分類のために,決定木・K 近傍・SVM (Support Vector Machine) の 3 つのアルゴリズムを検証した.検証の結果,研究所が保有する診療録の画像分類においては,SVM が正解率等において優位な結果を示した.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1288","bibliographic_titles":[{"bibliographic_title":"マルチメディア,分散協調とモバイルシンポジウム2021論文集"}],"bibliographicPageStart":"1285","bibliographicIssueDates":{"bibliographicIssueDate":"2021-06-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":213079,"updated":"2025-01-19T17:16:59.651143+00:00","links":{},"created":"2025-01-19T01:13:59.608890+00:00"}