Modelling of the relationship between systolic blood pressure and glucose with the magnesium ion present in the blood plasma: an approach using artificial neural networks

ISSN Print: 1949-4998
ISSN Online: 1949-5005
www.scirp.net/journal/health
E-mail: [email protected]

Citations

"Modelling of the relationship between systolic blood pressure and glucose with the magnesium ion present in the blood plasma: an approach using artificial neural networks"
written by Júlio C. D. Conway, Stefania N. Lavorato, Vinícius F. Cunha, Jadson C. Belchior,
published by Health, Vol.1 No.3, 2009

has been cited by the following article(s):

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[1]	Predicted Blood Pressure using Machine Learning 2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON), 2023 DOI:10.1109/SMARTGENCON60755.2023.10442670

[2]	An optimized spectral neural classification model based on multiple kernel fork joining clustering for premature treatment in health care industries Materials Today: Proceedings, 2021 DOI:10.1016/j.matpr.2020.12.863

[3]	An Empirical Study on Predicting Blood Pressure Using Classification and Regression Trees IEEE Access, 2018 DOI:10.1109/ACCESS.2017.2787980

[4]	Pharmacodynamic model of neuroendocrine controlled blood pressure 2016 International Conference on Microelectronics, Computing and Communications (MicroCom), 2016 DOI:10.1109/MicroCom.2016.7522555

[5]	A prediction model of blood pressure for telemedicine Health Informatics Journal, 2016 DOI:10.1177/1460458216663025

[6]	Bio-medical Application on Predicting Systolic Blood Pressure Using Neural Networks 2015 IEEE First International Conference on Big Data Computing Service and Applications, 2015 DOI:10.1109/BigDataService.2015.54

[7]	Predicting Systolic Blood Pressure Using Machine Learning 7th International Conference on Information and Automation for Sustainability, 2014 DOI:10.1109/ICIAFS.2014.7069529