{"created":"2024-12-12T08:03:02.061154+00:00","id":2010359,"links":{},"metadata":{"_buckets":{"deposit":"d3b32d1d-307f-404b-9d50-0c797736e152"},"_deposit":{"created_by":7,"id":"2010359","owners":[7],"pid":{"revision_id":0,"type":"depid","value":"2010359"},"status":"published"},"_oai":{"id":"oai:tokushima-u.repo.nii.ac.jp:02010359","sets":["1713853213384:1713853296295:1716267876683:1716268551628"]},"author_link":["1219","631","1183","1705","365","899"],"item_10001_alternative_title_1":{"attribute_name":"タイトル別表記","attribute_value_mlt":[{"subitem_alternative_title":"人工知能を用いた病院流動食の残量推定の精度 : 検証研究","subitem_alternative_title_language":"ja"}]},"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2022-05-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicPageStart":"e35991","bibliographicVolumeNumber":"6","bibliographic_titles":[{"bibliographic_title":"JMIR Formative Research","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Background: An accurate evaluation of the nutritional status of malnourished hospitalized patients at a higher risk of complications, such as frailty or disability, is crucial. Visual methods of estimating food intake are popular for evaluating the nutritional status in clinical environments. However, from the perspective of accurate measurement, such methods are unreliable.\nObjective: The accuracy of estimating leftover liquid food in hospitals using an artificial intelligence (AI)–based model was compared to that of visual estimation.\nMethods: The accuracy of the AI-based model (AI estimation) was compared to that of the visual estimation method for thin rice gruel as staple food and fermented milk and peach juice as side dishes. A total of 576 images of liquid food (432 images of thin rice gruel, 72 of fermented milk, and 72 of peach juice) were used. The mean absolute error, root mean squared error, and coefficient of determination (R2) were used as metrics for determining the accuracy of the evaluation process. Welch t test and the confusion matrix were used to examine the difference of mean absolute error between AI and visual estimation.\nResults: The mean absolute errors obtained through the AI estimation approach were 0.63 for fermented milk, 0.25 for peach juice, and 0.85 for the total. These were significantly smaller than those obtained using the visual estimation approach, which were 1.40 (P<.001) for fermented milk, 0.90 (P<.001) for peach juice, and 1.03 (P=.009) for the total. By contrast, the mean absolute error for thin rice gruel obtained using the AI estimation method (0.99) did not differ significantly from that obtained using visual estimation (0.99). The confusion matrix for thin rice gruel showed variation in the distribution of errors, indicating that the errors in the AI estimation were biased toward the case of many leftovers. The mean squared error for all liquid foods tended to be smaller for the AI estimation than for the visual estimation. Additionally, the coefficient of determination (R2) for fermented milk and peach juice tended to be larger for the AI estimation than for the visual estimation, and the R2 value for the total was equal in terms of accuracy between the AI and visual estimations.\nConclusions: The AI estimation approach achieved a smaller mean absolute error and root mean squared error and a larger coefficient of determination (R2) than the visual estimation approach for the side dishes. Additionally, the AI estimation approach achieved a smaller mean absolute error and root mean squared error compared to the visual estimation method, and the coefficient of determination (R2) was similar to that of the visual estimation method for the total. AI estimation measures liquid food intake in hospitals more precisely than visual estimation, but its accuracy in estimating staple food leftovers requires improvement.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"JMIR Publications","subitem_publisher_language":"en"}]},"item_10001_rights_15":{"attribute_name":"権利情報","attribute_value_mlt":[{"subitem_rights":"This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.","subitem_rights_language":"en"}]},"item_10001_source_id_9":{"attribute_name":"収録物ID","attribute_value_mlt":[{"subitem_source_identifier":"2561326X","subitem_source_identifier_type":"ISSN"}]},"item_10001_version_type_20":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_be7fb7dd8ff6fe43","subitem_version_type":"NA"}]},"item_1714461018643":{"attribute_name":"報告番号","attribute_value_mlt":[{"subitem_dissertationnumber":"甲第3690号"}]},"item_1714461102074":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士（医学）","subitem_degreename_language":"ja"}]},"item_1714461118377":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2023-03-23"}]},"item_1714461137393":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_language":"ja","subitem_degreegrantor_name":"徳島大学"}]}]},"item_1715043197608":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access"}]},"item_1718868208704":{"attribute_name":"備考","attribute_value_mlt":[{"subitem_textarea_language":"ja","subitem_textarea_value":"内容要旨・審査要旨・論文本文の公開\n本論文は，著者Masato Tagiの学位論文として提出され，学位審査・授与の対象となっている。\n学位授与者所属 : 徳島大学大学院医学研究科（医学専攻）"}]},"item_1718868303842":{"attribute_name":"学位記番号","attribute_value_mlt":[{"subitem_text_language":"ja","subitem_text_value":"甲医第1555号"}]},"item_1722929371688":{"attribute_name":"出版社版DOI","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_language":"ja","subitem_relation_name_text":"10.2196/35991"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.2196/35991","subitem_relation_type_select":"DOI"}}]},"item_1723180141928":{"attribute_name":"EID","attribute_value_mlt":[{"subitem_identifier_type":"URI","subitem_identifier_uri":"387992"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"田木, 真和","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"1219","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"タジリ, マリ","creatorNameLang":"ja"},{"creatorName":"タジリ, マリ","creatorNameLang":"ja-Kana"},{"creatorName":"Tajiri, Mari","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"濵田, 康弘","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"631","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"若田, 好史","creatorNameLang":"ja"},{"creatorName":"ワカタ, ヨシフミ","creatorNameLang":"ja-Kana"},{"creatorName":"Wakata, Yoshifumi","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"単, 暁","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"1183","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"尾崎, 和美","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"1705","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"クボタ, マサノリ","creatorNameLang":"ja"},{"creatorName":"クボタ, マサノリ","creatorNameLang":"ja-Kana"},{"creatorName":"Kubota, Masanori","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"アマノ, ソウスケ","creatorNameLang":"ja"},{"creatorName":"アマノ, ソウスケ","creatorNameLang":"ja-Kana"},{"creatorName":"Amano, Sosuke","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"阪上, 浩","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"365","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"鈴木, 佳子","creatorNameLang":"ja"},{"creatorName":"スズキ, ヨシコ","creatorNameLang":"ja-Kana"},{"creatorName":"Suzuki, Yoshiko","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"廣瀬, 隼","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"899","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-06-14"}],"displaytype":"detail","filename":"k3690_abstract.pdf","filesize":[{"value":"134 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"abstract","url":"https://tokushima-u.repo.nii.ac.jp/record/2010359/files/k3690_abstract.pdf"},"version_id":"b2f13adb-7fbf-4821-bea9-529277f223b8"},{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-06-14"}],"displaytype":"detail","filename":"k3690_review.pdf","filesize":[{"value":"120 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"other","url":"https://tokushima-u.repo.nii.ac.jp/record/2010359/files/k3690_review.pdf"},"version_id":"021f6355-6d4a-4999-8c35-b046aca21c83"},{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-06-14"}],"displaytype":"detail","filename":"k3690_fulltext.pdf","filesize":[{"value":"1.74 MB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://tokushima-u.repo.nii.ac.jp/record/2010359/files/k3690_fulltext.pdf"},"version_id":"fc4953c1-878c-4cda-adf6-21b1348c5964"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"artificial intelligence","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"convolutional neural network","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"food intake","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"liquid food","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"nutrition management","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"neural network","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"machine learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"malnourished","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"malnourishment","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"model","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"hospital","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"patient","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"nutrition","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"food consumption","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"dietary intake","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"diet","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"doctoral thesis","resourceuri":"http://purl.org/coar/resource_type/c_db06"}]},"item_title":"Accuracy of an Artificial Intelligence–Based Model for Estimating Leftover Liquid Food in Hospitals : Validation Study","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Accuracy of an Artificial Intelligence–Based Model for Estimating Leftover Liquid Food in Hospitals : Validation Study","subitem_title_language":"en"}]},"item_type_id":"40001","owner":"7","path":["1716268551628"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2022-11-25"},"publish_date":"2022-11-25","publish_status":"0","recid":"2010359","relation_version_is_last":true,"title":["Accuracy of an Artificial Intelligence–Based Model for Estimating Leftover Liquid Food in Hospitals : Validation Study"],"weko_creator_id":"7","weko_shared_id":-1},"updated":"2024-12-12T08:03:12.204742+00:00"}