Abstract:
Now a day in our world, heart diseases are the number one major cause of death. Statistics says that about 80% of deaths occurred in low- and middle income countries. Ifcurrenttrendsareallowedtocontinue,by2030anestimated23.6millionpeoplewill die from cardiovascular disease (mainly from heart attacks and strokes). The health care industry gathers enormous amounts of heart disease data which, unfortunately, are not ”mined” to discover hidden information for effective decision making. The reductionofbloodandoxygensupplytotheheartleadstoheartdisease.However,there is a lack of effective analysis tools to discover hidden relationships and trends in data. This research paper intends to provide a survey of current techniques of knowledge discovery in databases using data mining techniques which will be useful for medical practitionerstotakeeffectivedecision. Theobjectiveofthisresearchworkistopredict more accurately the presence of heart disease with reduced number of attributes.
Description:
We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Ourheartiestgratitude,profoundindebtednessanddeeprespectgotooursupervisor, Dr. Hasan Sarwar, Professor , Department of Computer Science and Engineering (CSE), United International University (UIU), Dhaka, Bangladesh, for his constant supervision, affectionate guidance and great encouragement and motivation. His keen interest on the topic and valuable advices throughout the study was of great help in completing thesis.
We are especially grateful to the Department of Computer Science and Engineering (CSE) of Military Institute of Science and Technology (MIST) for providing their all out support during the thesis work.
Finally, we would like to thank our families and our course mates for their appreciable assistance, patience and suggestions during the course of our thesis.
