Item type |
学術雑誌論文 / Journal Article(1) |
公開日 |
2019-05-27 |
タイトル |
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タイトル |
Study Protocol for the Effects of Artificial Intelligence (AI)-Supported Automated Nutritional Intervention on Glycemic Control in Patients with Type 2 Diabetes Mellitus |
言語 |
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言語 |
eng |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
ID登録 |
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ID登録 |
10.24517/00053790 |
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ID登録タイプ |
JaLC |
著者 |
Oka, Rie
Nomura, Akihiro
Yasugi, Ayaka
Kometani, Mitsuhiro
Gondoh, Yuko
Yoshimura, Kenichi
Yoneda, Takashi
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著者別表示 |
大家, 理恵
野村, 章洋
米谷, 充弘
吉村, 健一
米田, 隆
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提供者所属 |
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内容記述タイプ |
Other |
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内容記述 |
金沢大学融合研究域融合科学系 / 金沢大学附属病院代謝内科 |
書誌情報 |
Diabetes Therapy
巻 10,
号 3,
p. 1151-1161,
発行日 2019-06
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ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
1869-6953 |
DOI |
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関連タイプ |
isIdenticalTo |
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識別子タイプ |
DOI |
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関連識別子 |
10.1007/s13300-019-0595-5 |
出版者 |
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出版者 |
Springer (part of Springer Nature) |
抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Nutritional intervention is effective in improving glycemic control in patients with type 2 diabetes but requires large inputs of manpower. Recent improvements in photo analysis technology facilitated by artificial intelligence (AI) and remote communication technologies have enabled automated evaluations of nutrient intakes. AI- and mobile-supported nutritional intervention is expected to be an alternative approach to conventional in-person nutritional intervention, but with less human resources, although supporting evidence is not yet complete. The aim of this study is to test the hypothesis that AI-supported nutritional intervention is as efficacious as the in-person, face-to-face method in terms of improving glycemic control in patients with type 2 diabetes. |
権利 |
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権利情報 |
Copyright © The Author(s) 2019 |
著者版フラグ |
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出版タイプ |
VoR |
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出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
関連URI |
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識別子タイプ |
URI |
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関連識別子 |
https://link.springer.com/article/10.1007/s13300-019-0595-5 |
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関連名称 |
https://link.springer.com/article/10.1007/s13300-019-0595-5 |