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Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining.
Liu, Fan; Zhou, Xingshe; Wang, Zhu; Cao, Jinli; Wang, Hua; Zhang, Yanchun.
Affiliation
  • Liu F; School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China. liufant800@mail.nwpu.edu.cn.
  • Zhou X; College of Engineering and Science, Victoria University, Melbourne, VIC 3011, Australia. liufant800@mail.nwpu.edu.cn.
  • Wang Z; School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China. zhouxs@nwpu.edu.cn.
  • Cao J; School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China. wangzhu@nwpu.edu.cn.
  • Wang H; Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC 3086, Australia. J.Cao@latrobe.edu.au.
  • Zhang Y; College of Engineering and Science, Victoria University, Melbourne, VIC 3011, Australia. Hua.Wang@vu.edu.au.
Sensors (Basel) ; 19(7)2019 Mar 27.
Article in En | MEDLINE | ID: mdl-30934719
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Beds / Data Mining / Hypertension Type of study: Diagnostic_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Sensors (Basel) Year: 2019 Type: Article Affiliation country: China
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Beds / Data Mining / Hypertension Type of study: Diagnostic_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Sensors (Basel) Year: 2019 Type: Article Affiliation country: China