{"created":"2025-01-16T01:51:40.136478+00:00","id":2012394,"links":{},"metadata":{"_buckets":{"deposit":"9f7ffdce-bb4d-48a2-9d70-e6384d01ab97"},"_deposit":{"created_by":7,"id":"2012394","owners":[7],"pid":{"revision_id":0,"type":"depid","value":"2012394"},"status":"published"},"_oai":{"id":"oai:tokushima-u.repo.nii.ac.jp:02012394","sets":["1713853213384:1713853295607"]},"author_link":["631","899","1183","365","1705","1219"],"control_number":"2012394","item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2024-11-05","bibliographicIssueDateType":"Issued"},"bibliographicPageStart":"e55218","bibliographicVolumeNumber":"8","bibliographic_titles":[{"bibliographic_title":"JMIR Formative Research","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Background: Medical staff often conduct assessments, such as food intake and nutrient sufficiency ratios, to accurately evaluate patients’ food consumption. However, visual estimations to measure food intake are difficult to perform with numerous patients. Hence, the clinical environment requires a simple and accurate method to measure dietary intake.\nObjective: This study aims to develop a food intake estimation system through an artificial intelligence (AI) model to estimate leftover food. The accuracy of the AI’s estimation was compared with that of visual estimation for liquid foods served to hospitalized patients.\nMethods: The estimations were evaluated by a dietitian who looked at the food photo (image visual estimation) and visual measurement evaluation was carried out by a nurse who looked directly at the food (direct visual estimation) based on actual measurements. In total, 300 dishes of liquid food (100 dishes of thin rice gruel, 100 of vegetable soup, 31 of fermented milk, and 18, 12, 13, and 26 of peach, grape, orange, and mixed juices, respectively) were used. The root-mean-square error (RMSE) and coefficient of determination (R2) were used as metrics to determine the accuracy of the evaluation process. Corresponding t tests and Spearman rank correlation coefficients were used to verify the accuracy of the measurements by each estimation method with the weighing method.\nResults: The RMSE obtained by the AI estimation approach was 8.12 for energy. This tended to be smaller and larger than that obtained by the image visual estimation approach (8.49) and direct visual estimation approach (4.34), respectively. In addition, the R2 value for the AI estimation tended to be larger and smaller than the image and direct visual estimations, respectively. There was no difference between the AI estimation (mean 71.7, SD 23.9 kcal, P=.82) and actual values with the weighing method. However, the mean nutrient intake from the image visual estimation (mean 75.5, SD 23.2 kcal, P<.001) and direct visual estimation (mean 73.1, SD 26.4 kcal, P=.007) were significantly different from the actual values. Spearman rank correlation coefficients were high for energy (ρ=0.89-0.97), protein (ρ=0.94-0.97), fat (ρ=0.91-0.94), and carbohydrate (ρ=0.89-0.97).\nConclusions: The measurement from the food intake estimation system by an AI-based model to estimate leftover liquid food intake in patients showed a high correlation with the actual values with the weighing method. Furthermore, it also showed a higher accuracy than the image visual estimation. The errors of the AI estimation method were within the acceptable range of the weighing method, which indicated that the AI-based food intake estimation system could be applied in clinical environments. However, its lower accuracy than that of direct visual estimation was still an issue.","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":"EISSN"}]},"item_10001_version_type_20":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1715043197608":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open 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Yasuhiro","creatorNameLang":"en"}],"familyNames":[{"familyName":"濵田","familyNameLang":"ja"},{"familyName":"ハマダ","familyNameLang":"ja-Kana"},{"familyName":"Hamada","familyNameLang":"en"}],"givenNames":[{"givenName":"康弘","givenNameLang":"ja"},{"givenName":"ヤスヒロ","givenNameLang":"ja-Kana"},{"givenName":"Yasuhiro","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"631","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"261537/profile-ja.html","nameIdentifierScheme":"徳島大学 教育研究者総覧","nameIdentifierURI":"http://pub2.db.tokushima-u.ac.jp/ERD/person/261537/profile-ja.html"},{"nameIdentifier":"30397830","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?qm=30397830"}]},{"creatorNames":[{"creatorName":"単, 暁","creatorNameLang":"ja"},{"creatorName":"タン, ギョウ","creatorNameLang":"ja-Kana"},{"creatorName":"Shan, 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Kazumi","creatorNameLang":"en"}],"familyNames":[{"familyName":"尾崎","familyNameLang":"ja"},{"familyName":"オザキ","familyNameLang":"ja-Kana"},{"familyName":"Ozaki","familyNameLang":"en"}],"givenNames":[{"givenName":"和美","givenNameLang":"ja"},{"givenName":"カズミ","givenNameLang":"ja-Kana"},{"givenName":"Kazumi","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"1705","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"60420/profile-ja.html","nameIdentifierScheme":"徳島大学 教育研究者総覧","nameIdentifierURI":"http://pub2.db.tokushima-u.ac.jp/ERD/person/60420/profile-ja.html"},{"nameIdentifier":"90214121","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/search/?qm=90214121"}]},{"creatorNames":[{"creatorName":"Kubota, Masanori","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Amano, Sosuke","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"阪上, 浩","creatorNameLang":"ja"},{"creatorName":"サカウエ, ヒロシ","creatorNameLang":"ja-Kana"},{"creatorName":"Sakaue, 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ジュン","creatorNameLang":"ja-Kana"},{"creatorName":"Hirose, Jun","creatorNameLang":"en"}],"familyNames":[{"familyName":"廣瀬","familyNameLang":"ja"},{"familyName":"ヒロセ","familyNameLang":"ja-Kana"},{"familyName":"Hirose","familyNameLang":"en"}],"givenNames":[{"givenName":"隼","givenNameLang":"ja"},{"givenName":"ジュン","givenNameLang":"ja-Kana"},{"givenName":"Jun","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"899","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"334007/profile-ja.html","nameIdentifierScheme":"徳島大学 教育研究者総覧","nameIdentifierURI":"http://pub2.db.tokushima-u.ac.jp/ERD/person/334007/profile-ja.html"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2025-01-31"}],"displaytype":"detail","filename":"jmirfr_8_e55218.pdf","filesize":[{"value":"1.6 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consumption","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"image visual estimation","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"AI estimation","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"direct visual estimation","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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"A Food Intake Estimation System Using an Artificial Intelligence–Based Model for Estimating Leftover Hospital Liquid Food in Clinical Environments : Development and Validation Study","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A Food Intake Estimation System Using an Artificial Intelligence–Based Model for Estimating Leftover Hospital Liquid Food in Clinical Environments : Development and Validation Study","subitem_title_language":"en"}]},"item_type_id":"40001","owner":"7","path":["1713853295607"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-01-31"},"publish_date":"2025-01-31","publish_status":"0","recid":"2012394","relation_version_is_last":true,"title":["A Food Intake Estimation System Using an Artificial Intelligence–Based Model for Estimating Leftover Hospital Liquid Food in Clinical Environments : Development and Validation Study"],"weko_creator_id":"7","weko_shared_id":-1},"updated":"2025-02-03T06:41:46.227695+00:00"}