Abstract:
The thesis aims to develop a way of finding out the trends that might exist between different
cardiovascular diseases(CVD) 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 thesis also suggests a new centralized healthcare structure. The thesis 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 paper 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. After gathering this
information data mining algorithms are used to find the possible trends between these diseases
and other aspects of patients life. By identification of these patterns possible preventive measures
and reorientation of health care facilities are suggested for the betterment of society.
