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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Using Neural Network to predict the Hypertension |
| Authors Name: | Zainab Assaghir , Ali Janbain , Sara Makki , Mazen Kurdi , Rita Karam |
| Unique Id: | IJSDR1702009 |
| Published In: | Volume 2 Issue 2, February-2017 |
| Abstract: | Development of tools to facilitate diagnosis of some disease such as cancer, cardiovascular, hypertension, diabetes, is of great relevance in the medical field. In this paper, we will present a method based on neural network to detect the hypertension based on some risk factors including obesity, stress, systolic and diastolic blood pressure, physical activities, tobacco consumption and diet lifestyle. Data represents a group of students from the Lebanese universities. A descriptive statistical analysis is performed then a neural network predicting systolic and diastolic blood pressure is designed and implemented. Descriptive statistics show some difference between male and female groups. Tobacco consumption is mostly present in the male group more than female. In the other hand, the neural network consists of ten inputs and two outputs. The outcomes of the network are diastolic and systolic blood pressure. Accurate results have been obtained which proves the effectiveness of the proposed neural networks can be effective tools for preliminary detection of hypertension. |
| Keywords: | Neural Network, Hypertension, Medical Diagnosis; Artificial Intelligence |
| Cite Article: | "Using Neural Network to predict the Hypertension", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.2, Issue 2, page no.35 - 38, February-2017, Available :http://www.ijsdr.org/papers/IJSDR1702009.pdf |
| Downloads: | 000337070 |
| Publication Details: | Published Paper ID: IJSDR1702009 Registration ID:170033 Published In: Volume 2 Issue 2, February-2017 DOI (Digital Object Identifier): Page No: 35 - 38 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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