Developed a machine learning model to predict heart disease. Linked this model to a Web Aplication to make it available for users to check their heart health.
We have obtained the dataset from Kaggle. It has patient medical records with 13 parameters/columns useful to predict heart health.
The 13 parameters which are given in the datset used to predict if a person has heart disease or not are:
- age : The person's age in years
- sex : The person's sex (1 = male, 0 = female)
- cp : The chest pain experienced (Value 1: typical angina, Value 2: atypical angina, Value 3: non-anginal pain, Value 4: asymptomatic)
- trestbps : The person's resting blood pressure (mm Hg on admission to the hospital)
- chol : The person's cholesterol measurement in mg/dl
- fbs : The person's fasting blood sugar (> 120 mg/dl, 1 = true; 0 = false)
- restecg : Resting electrocardiographic measurement (0 = normal, 1 = having ST-T wave abnormality, 2 = showing probable or definite left ventricular hypertrophy by Estes' criteria
- thalach : The person's maximum heart rate achieved
- exang : Exercise induced angina (1 = yes; 0 = no)
- oldpeak : ST depression induced by exercise relative to rest ('ST' relates to positions on the ECG plot)
- slope : the slope of the peak exercise ST segment (Value 1: upsloping, Value 2: flat, Value 3: downsloping)
- ca : The number of major vessels (0-3)
- thal : A blood disorder called thalassemia (3 = normal; 6 = fixed defect; 7 = reversable defect)
The last column in the dataset "target" represents if a person has hear disease or not (1 = Heart disease, 0 = No Heart disease).
After training and testing the dataset with KNN, Logistic Regression and Linear Regression and Naive Bayes and comparing their accuracies, chose to use Logistic Regression for implentation.
Then saved this model and using Flask for backend linked this model to a website.
Users can just enter the 13 parameters in the form and press submit to obtain the probability of whether their heart is prone to any disease or not.
How to RUN the Project:
- Install necessary packages such as Flask, Numpy etc.
- Then type in the command
python app.py
Here are some screenshots of the website
