Chinese diabetes datasets for data-driven machine learning

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorZhao, Qinpeien_US
dc.contributor.authorZhu, Jinhaoen_US
dc.contributor.authorShen, Xuanen_US
dc.contributor.authorLin, Chuwenen_US
dc.contributor.authorZhang, Yinjiaen_US
dc.contributor.authorLiang, Yuxiangen_US
dc.contributor.authorCao, Baigeen_US
dc.contributor.authorLi, Jiangfengen_US
dc.contributor.authorLiu, Xiangen_US
dc.contributor.authorRao, Weixiongen_US
dc.contributor.authorWang, Congrongen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.organizationTongji Universityen_US
dc.contributor.organizationZhejiang Yugu Medical Technology Ltden_US
dc.date.accessioned2023-02-20T05:12:36Z
dc.date.available2023-02-20T05:12:36Z
dc.date.issued2023-01-19en_US
dc.descriptionFunding Information: This work was supported by the National Natural Science Foundation of China (Grant No. 61972286, 82070913), the Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100), the Natural Science Foundation of Shanghai, China (Grant No. 20ZR1460500, 22511104300), the Shanghai Science and Technology Development Funds (Grant No. 20ZR1446000, 22410713200), the Fundamental Research Funds for the Central Universities and the Research fund from Shanghai Fourth People’s Hospital (sykyqd01801, SY-XKZT-2021-1001). Finally, thanks Ms. Xiongbaixue Yan for her previous efforts on the management of the project. Publisher Copyright: © 2023, The Author(s).
dc.description.abstractData of the diabetes mellitus patients is essential in the study of diabetes management, especially when employing the data-driven machine learning methods into the management. To promote and facilitate the research in diabetes management, we have developed the ShanghaiT1DM and ShanghaiT2DM Datasets and made them publicly available for research purposes. This paper describes the datasets, which was acquired on Type 1 (n = 12) and Type 2 (n = 100) diabetic patients in Shanghai, China. The acquisition has been made in real-life conditions. The datasets contain the clinical characteristics, laboratory measurements and medications of the patients. Moreover, the continuous glucose monitoring readings with 3 to 14 days as a period together with the daily dietary information are also provided. The datasets can contribute to the development of data-driven algorithms/models and diabetes monitoring/managing technologies.en
dc.description.versionPeer revieweden
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationZhao, Q, Zhu, J, Shen, X, Lin, C, Zhang, Y, Liang, Y, Cao, B, Li, J, Liu, X, Rao, W & Wang, C 2023, ' Chinese diabetes datasets for data-driven machine learning ', Scientific Data, vol. 10, no. 1, 35 . https://doi.org/10.1038/s41597-023-01940-7en
dc.identifier.doi10.1038/s41597-023-01940-7en_US
dc.identifier.issn2052-4463
dc.identifier.otherPURE UUID: 466eaf8b-4ff7-42bb-9f74-68cd5628efb9en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/466eaf8b-4ff7-42bb-9f74-68cd5628efb9en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85146485715&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/100206019/Chinese_diabetes_datasets_for_data_driven_machine_learning.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/119764
dc.identifier.urnURN:NBN:fi:aalto-202302202111
dc.language.isoenen
dc.publisherNature Publishing Group
dc.relation.ispartofseriesScientific Dataen
dc.relation.ispartofseriesVolume 10, issue 1en
dc.rightsopenAccessen
dc.titleChinese diabetes datasets for data-driven machine learningen
dc.typeData Articlefi
dc.type.versionpublishedVersion

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