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STORAGE AREA NETWORK FOR NATIONAL MEDICAL RECORDS AND DATA MINING FOR TREND ANALYSIS

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dc.contributor.author DR SHOAB A KHAN, AHMAD,HAARIS BIN GHAFOOR,ZAIN,IRFAN
dc.date.accessioned 2025-04-28T05:56:46Z
dc.date.available 2025-04-28T05:56:46Z
dc.date.issued 2011
dc.identifier.other DE-COMP-29
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/52461
dc.description Supervisor DR SHOAB A KHAN en_US
dc.description.abstract Cardiovascular Diseases are solely responsible for 50% of all deaths caused by NonCommunicable Diseases in Pakistan. It is an established fact that life style of a person effect his heart condition. Life style includes his socio-economic status, his demographic location and his previous and family medical history. Knowledge about these aspects of patients life can tell us a lot about the type of disease he is most suspected to become a target of. The project aims to develop a way of finding out the trends that might exist between different cardiovascular diseases and the socioeconomic, demographic and medical history of a patient. Thus enabling the health sector to prevent large number of deaths caused by such diseases each year. To achieve this goal the current structure of healthcare sector needs to be somewhat changed and hence this project also provides a new centralized healthcare structure. The project not only suggests ways of centralizing the healthcare structure of the country but also shows the ways in which it can be used in reducing CVD. A large portion of the project deals with reading the acquired ECG of a patient the way Minnesota ECG Code elaborates and then using this data to find the possible arrhythmia the patient might be suffering from. Once this information has been gathered data mining algorithms are used to find the possible trends between these diseases and other aspects of patients life. en_US
dc.language.iso en en_US
dc.publisher College of Electrical & Mechanical Engineering (CEME), NUST en_US
dc.title STORAGE AREA NETWORK FOR NATIONAL MEDICAL RECORDS AND DATA MINING FOR TREND ANALYSIS en_US
dc.type Project Report en_US


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