Disease Prediction System is a machine learning model for early diagnosis of heart and diabetes diseases.
Cardiovascular disease and diabetes are the most common cause of death worldwide over the last few decades in the developed as well as underdeveloped and developing countries. Early detection of these diseases can reduce the mortality rate. However, it is not possible to monitor patients every day in all cases accurately and consultation of a patient for 24 hours by doctor is not available since it requires more sapience, time and expertise.
In this project, we have developed a heart disease and diabetes prediction system (model) trained using support vector machine and Logistic Regression.
The early prognosis of cardiovascular and diabetes disease can aid in making decisions on lifestyle changes in high risk patients and in turn reduce the complications, which can be a great milestone in the field of medicine.
Keywords: Machine Learning; Logistic Regression; SVM; Cardiovascular Diseases; Diabetes Diseases
The project consists of two models:
i. Heart Disease Prediction
ii. Diabetes Disease Prediction
Algorithms used in our projects are:
- Logistic Regression
It is supervised classification algorithm used in heart disease prediction system. - Support Vector Machine Classifier (SVM)
For the Diabetes disease prediction system.
- Sonam Pelki (https://gitlab.com/12200081.gcit)
- Pema Dendup (https://gitlab.com/Mtee405)
- Ugyen Kezang (https://gitlab.com/Ugyen94)
- Ugyen Lhamo (https://gitlab.com/ugyen_lha731)
https://www.canva.com/design/DAFT-cROLjY/9s8VsRNphQZcNnK5VXSyjg/edit