Data Classification of Heart Disease
Heart Disease refers to a various type of conditions that affect the heart. Because of this heart attack 4,500 and 5,000 people are hospitalized each year in Mauritius. Both men and women have different symptoms of heart disease. For example men have chest pain more often and women have other symptoms like chest discomfort. Young people are more affected by it. Age 40 to 60 years, we have 40% of people who have heart disease. The number of death due to heart disease worldwide is estimates at 17.5 million, which means 31% death in total. Therefore it is important to search for solution to combat this heart disease. The causes of heart disease are as follows:
Cardiomyopathy is a disease of the heart muscle which leads to heart failure. The heart muscle makes the heart difficult to pump blood to the entire body.
Coronary Artery Disease
CAD is a serious disease which sometimes leads to death. It damages the major blood vessels that supply the heart with oxygen, nutrients and blood.
Diabetes can cause many diseases including heart disease. Diabetes also increases level of glucose in the blood.
Diseases of the Heart Valves
Diseases of the Heart Valves develop when the heart which involve four valves do not work in the correctly direction or properly.
Congenital Heart Defects which is here at birth
CHD is a heart problem which is here at birth. It is caused at early week of pregnancy by abnormal formation of the heart.
High Blood Pressure
High Blood Pressure is the measure of force of blood against the artery wall. Heart Blood Pressure is easily detected and can be treated or control with the help of doctors.
Lung Disease like Emphysema
Past Heart Attack
Data mining techniques are normally used in large data set in order to extract information from medical data bases. Data mining is also called data discovery and knowledge discovery. The advantage of data mining is that it helps in discovering hidden patterns and connection in data. These patterns and connections are used to predict results for future use. The functionality of data mining is association, classification, prediction, tracking pattern and decision tree.
To increase the potential of making medical decision, data mining techniques are applied to different medical categories. In many hospitals, we are looking for a way to improve the service and quality of heart disease patients and their affordable cost. In this case, data mining techniques are the solution to the problem concerning the health for the diagnosing patients.
Classification is one of the important techniques of data mining. Data Classification is the process of sorting and categorizing data so that it may be used and protected more efficiently. The purpose of data classification is to support data security, ease of access and also data must be easy to search and retrieve within specified period of time. Data Classification helps us identity relationship between the data that we may not see at a whole. The type of classification algorithms on Machine Language are:
Linear Classifier that is Logistic Regression and Naïve Bayes Classifier
Linear Classifier uses the value of a linear combination of the characteristics to make classification decision. Logistic Regression and Naïve Bayes Classifier are both linear classification where Logistic Regression uses a direct functional form to make forecast about the probability and Naïve Bayes use the results to find out how the data was generated.
Support Vector Machines