Prediction system for determination of hypertension risk using artificial neural network / Nur Izzati Zulkifli

Zulkifli, Nur Izzati (2012) Prediction system for determination of hypertension risk using artificial neural network / Nur Izzati Zulkifli. Degree thesis, Universiti Teknologi MARA,Terengganu.

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Abstract

There are a lot oftechniques that can be used to make predictions, but the technique which is suitable to be used to make this prediction is Artificial Neural Network system. Back-propagation is one ofthe feed-forward techniques that can be used when we know what the output that will carry out after the data keyed in. this problem also occurs in adolescents and children. Many who know this disease is caused by the existing symptoms such as severe headaches, nose bleeds, blurred vision, palpitations and stress. The objective ofthe research, firstly, to understand about determination the hypertension risk using Artificial Neural Network, secondly, to propose prediction model of Hypertension risk using Artificial Neural Network engine. Lastly, to test and evaluate new data Hypertension's Patient using prediction model. The Prediction used in Neural Network technique is whereby some of the data about the parameter of Hypertension like age, BMI level, Blood Pressure(Systolic and Diastolic), Smoking Habit and Family History to see whether the persons have hypertension or not. As a result of this project, the system is user friendly and easy to use especially the doctor to check their patient have hypertension or not before get treatment or other people to check their hypertension disease.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email
Zulkifli, Nur Izzati
2010417928
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Engku Azam, Engku Zain
UNSPECIFIED
Subjects: Q Science > Q Science (General) > Back propagation (Artificial intelligence)
Q Science > Q Science (General) > Back propagation (Artificial intelligence) > Malaysia
R Medicine > RC Internal Medicine > Hypertension
Divisions: Universiti Teknologi MARA, Terengganu > Dungun Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Computer Science (Hons)
Item ID: 35113
Uncontrolled Keywords: hypertension; artificial neural network; Back-propagation
URI: https://ir.uitm.edu.my/id/eprint/35113

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