Chinese diabetes datasets for data-driven machine learning
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.author | Zhao, Qinpei | en_US |
dc.contributor.author | Zhu, Jinhao | en_US |
dc.contributor.author | Shen, Xuan | en_US |
dc.contributor.author | Lin, Chuwen | en_US |
dc.contributor.author | Zhang, Yinjia | en_US |
dc.contributor.author | Liang, Yuxiang | en_US |
dc.contributor.author | Cao, Baige | en_US |
dc.contributor.author | Li, Jiangfeng | en_US |
dc.contributor.author | Liu, Xiang | en_US |
dc.contributor.author | Rao, Weixiong | en_US |
dc.contributor.author | Wang, Congrong | en_US |
dc.contributor.department | Department of Computer Science | en |
dc.contributor.organization | Tongji University | en_US |
dc.contributor.organization | Zhejiang Yugu Medical Technology Ltd | en_US |
dc.date.accessioned | 2023-02-20T05:12:36Z | |
dc.date.available | 2023-02-20T05:12:36Z | |
dc.date.issued | 2023-01-19 | en_US |
dc.description | Funding 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.abstract | Data 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.version | Peer reviewed | en |
dc.format.mimetype | application/pdf | en_US |
dc.identifier.citation | Zhao, 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/s41597-023-01940-7 | en |
dc.identifier.doi | 10.1038/s41597-023-01940-7 | en_US |
dc.identifier.issn | 2052-4463 | |
dc.identifier.other | PURE UUID: 466eaf8b-4ff7-42bb-9f74-68cd5628efb9 | en_US |
dc.identifier.other | PURE ITEMURL: https://research.aalto.fi/en/publications/466eaf8b-4ff7-42bb-9f74-68cd5628efb9 | en_US |
dc.identifier.other | PURE LINK: http://www.scopus.com/inward/record.url?scp=85146485715&partnerID=8YFLogxK | en_US |
dc.identifier.other | PURE FILEURL: https://research.aalto.fi/files/100206019/Chinese_diabetes_datasets_for_data_driven_machine_learning.pdf | en_US |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/119764 | |
dc.identifier.urn | URN:NBN:fi:aalto-202302202111 | |
dc.language.iso | en | en |
dc.publisher | Nature Publishing Group | |
dc.relation.ispartofseries | Scientific Data | en |
dc.relation.ispartofseries | Volume 10, issue 1 | en |
dc.rights | openAccess | en |
dc.title | Chinese diabetes datasets for data-driven machine learning | en |
dc.type | Data Article | fi |
dc.type.version | publishedVersion |