Analyzing Heart Disease using Patient Medical Records
Date:
Key words : SAS, Descriptive Statistics , Logistic Regression, Discriminant Analysis
Health sciences is one of the areas where Data analysis plays a crucial role and it offers rich medical records data for the patients. By analyzing the patient’s historical data, we can find some interesting insights about a certain disease, which will benefit in predicting a new patient getting a similar disease. So, that we can take necessary actions possible to prevent the disease or else we can treat the disease effectively by identifying the major cause.
For this group project, Jay was the leader of the group and guide small team of under-graduate students.Our group choose to work on chronic heart disease and it is one of major disease that causes thousands of deaths. Through Data modelling on patient data we try to predict the chances of a patient getting chronic heart disease. Also, we figure out what are the major factors that cause heart disease, and tried to answer questions like
1) Is the heart disease depends on Age of the patient, then what is the age range that is more prone to the heart disease?
2) What are the effects of Smoking and drinking habits, and do they most likely cause heart disease
3) How obesity or cholesterol, effects the chances of getting a heart disease?
4) Does the heart disease depended on family history? i.e; If any family member has the heart disease then how likely it is, patient getting a heart disease.
Jay’s role in this project was to lead the team through guidance and discussions ,building predictive model for hereditary factor using Discriminant analysis and interpret ,visualize the effect of significant variables causing heart disease.More details can be found on links below
Links : Project report and Git Repository