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

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ISSN Print: 1949-4998
ISSN Online: 1949-5005
www.scirp.org/journal/health
E-mail: health@scirp.org

"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

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[1]	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

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

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

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

[5]	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

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

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