Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/330508
Title: Study on Fusion Methodology for Diagnosis of Hypertension Using Neural Networks
Researcher: Sumathi, B
Guide(s): Santhakumaran, A
Keywords: Computer Science
Computer Science Artificial Intelligence
Engineering and Technology
University: Mother Teresa Womens University
Completed Date: 2017
Abstract: newline Medical diagnosis of diseases is complex in nature. Computerized diagnostic tools have received significant attention over the past few decades to assist medical practitioners in the diagnosis of diseases. Medical decision support systems are one of the main applications of machine learning techniques. The physician uses his knowledge in the subjects, expertise and talent in order to diagnose the disease. A diagnostic procedure starts with the patient s complaints and the doctor learns more about patient s situation. Hypertension is the major risk factor for other diseases, thus it is a domain requiring attention, in health care system. In order to decrease the risk of hypertension early screening of patients before they get its symptoms can be an effective solution. Hypertension is a most serious disease that affects a wide range of the population, especially the elderly after the age of 50. Individuals with the age of more than 50 have 90% lifetime risk of developing hypertension. Accurate measurement of blood pressure is essential in the diagnosis and treatment of hypertension. The amount of data coming from clinical analysis of the diseases is quite large.
Pagination: 181p.
URI: http://hdl.handle.net/10603/330508
Appears in Departments:Department of Computer Science

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80_recommendation.pdf123 kBAdobe PDFView/Open
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