Blood Pressure Classification Using the Method of the Modular Neural Networks
In this paper, we present a new model based on modular neural networks (MNN) to classify a patient’s blood pressure level (systolic and diastolic pressure and pulse). Tests are performed with the Levenberg-Marquardt (trainlm) and scaled conjugate gradient backpropagation (traincsg) training methods....
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | International Journal of Hypertension |
| Online Access: | http://dx.doi.org/10.1155/2019/7320365 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849405925046091776 |
|---|---|
| author | Martha Pulido Patricia Melin German Prado-Arechiga |
| author_facet | Martha Pulido Patricia Melin German Prado-Arechiga |
| author_sort | Martha Pulido |
| collection | DOAJ |
| description | In this paper, we present a new model based on modular neural networks (MNN) to classify a patient’s blood pressure level (systolic and diastolic pressure and pulse). Tests are performed with the Levenberg-Marquardt (trainlm) and scaled conjugate gradient backpropagation (traincsg) training methods. The modular neural network architecture is formed by three modules. In the first module we consider the diastolic pressure data; in the second module we use details of the systolic pressure; in the third module, pulse data is used and the response integration is performed with the average method. The goal is to design the best MNN architecture for achieving an accurate classification. The results of the model show that MNN presents an excellent classification for blood pressure. The contribution of this work is related to helping the cardiologist in providing a good diagnosis and patient treatment and allows the analysis of the behavior of blood pressure in relation to the corresponding diagnosis, in order to prevent heart disease. |
| format | Article |
| id | doaj-art-52d62ed609a1445f856e6058984ea5ff |
| institution | Kabale University |
| issn | 2090-0384 2090-0392 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Hypertension |
| spelling | doaj-art-52d62ed609a1445f856e6058984ea5ff2025-08-20T03:36:34ZengWileyInternational Journal of Hypertension2090-03842090-03922019-01-01201910.1155/2019/73203657320365Blood Pressure Classification Using the Method of the Modular Neural NetworksMartha Pulido0Patricia Melin1German Prado-Arechiga2Tijuana Institute of Technology, Calzada Tecnológico, Tijuana 22379, MexicoTijuana Institute of Technology, Calzada Tecnológico, Tijuana 22379, MexicoCardiodiagnostico Excel Medial Center, Tijuana 22010, MexicoIn this paper, we present a new model based on modular neural networks (MNN) to classify a patient’s blood pressure level (systolic and diastolic pressure and pulse). Tests are performed with the Levenberg-Marquardt (trainlm) and scaled conjugate gradient backpropagation (traincsg) training methods. The modular neural network architecture is formed by three modules. In the first module we consider the diastolic pressure data; in the second module we use details of the systolic pressure; in the third module, pulse data is used and the response integration is performed with the average method. The goal is to design the best MNN architecture for achieving an accurate classification. The results of the model show that MNN presents an excellent classification for blood pressure. The contribution of this work is related to helping the cardiologist in providing a good diagnosis and patient treatment and allows the analysis of the behavior of blood pressure in relation to the corresponding diagnosis, in order to prevent heart disease.http://dx.doi.org/10.1155/2019/7320365 |
| spellingShingle | Martha Pulido Patricia Melin German Prado-Arechiga Blood Pressure Classification Using the Method of the Modular Neural Networks International Journal of Hypertension |
| title | Blood Pressure Classification Using the Method of the Modular Neural Networks |
| title_full | Blood Pressure Classification Using the Method of the Modular Neural Networks |
| title_fullStr | Blood Pressure Classification Using the Method of the Modular Neural Networks |
| title_full_unstemmed | Blood Pressure Classification Using the Method of the Modular Neural Networks |
| title_short | Blood Pressure Classification Using the Method of the Modular Neural Networks |
| title_sort | blood pressure classification using the method of the modular neural networks |
| url | http://dx.doi.org/10.1155/2019/7320365 |
| work_keys_str_mv | AT marthapulido bloodpressureclassificationusingthemethodofthemodularneuralnetworks AT patriciamelin bloodpressureclassificationusingthemethodofthemodularneuralnetworks AT germanpradoarechiga bloodpressureclassificationusingthemethodofthemodularneuralnetworks |