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Body composition predicts hypertension using machine learning methods: a cohort study.
Nematollahi, Mohammad Ali; Jahangiri, Soodeh; Asadollahi, Arefeh; Salimi, Maryam; Dehghan, Azizallah; Mashayekh, Mina; Roshanzamir, Mohamad; Gholamabbas, Ghazal; Alizadehsani, Roohallah; Bazrafshan, Mehdi; Bazrafshan, Hanieh; Bazrafshan Drissi, Hamed; Shariful Islam, Sheikh Mohammed.
Affiliation
  • Nematollahi MA; Department of Computer Sciences, Fasa University, Fasa, Iran.
  • Jahangiri S; Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Asadollahi A; Non Communicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.
  • Salimi M; Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Dehghan A; Bone and Joint Diseases Research Center, Department of Orthopedic Surgery, Shiraz University of Medical Science, Shiraz, Iran.
  • Mashayekh M; Non Communicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.
  • Roshanzamir M; Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Gholamabbas G; Department of Computer Engineering, Faculty of Engineering, Fasa University, Fasa, 74617-81189, Iran.
  • Alizadehsani R; Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Bazrafshan M; Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, Australia.
  • Bazrafshan H; Shiraz University of Medical Sciences, Shiraz, Iran.
  • Bazrafshan Drissi H; Department of Neurology, Clinical Neurology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Shariful Islam SM; Cardiovascular Research Center, Shiraz University of Medical Sciences, PO Box: 71348-14336, Shiraz, Iran. hamedbazrafshan@yahoo.com.
Sci Rep ; 13(1): 6885, 2023 04 27.
Article in En | MEDLINE | ID: mdl-37105977
Subject(s)
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Body Composition / Machine Learning Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Sci Rep Year: 2023 Document type: Article Affiliation country: Iran Country of publication: United kingdom
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Body Composition / Machine Learning Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Sci Rep Year: 2023 Document type: Article Affiliation country: Iran Country of publication: United kingdom