The problem Disease Analyser Product solves

Heart disease Prediction

Heart disease is one of the most significant problems that is arising in the world today.
Cardiovascular disease prediction is a critical challenge in the area of clinical data analysis. Hybrid Machine learning (ML) has been showing effective assistance in making decisions and predictions from the large quantity of data produced by healthcare hospitals.

Diabetes disease Prediction

Diabetes is a metabolic disease affecting a multitude of people worldwide. Its incidence rates are increasing alarmingly every year. If untreated, diabetes-related complications in many vital organs of the body may turn fatal. Early detection of diabetes is very important for timely treatment which can stop the disease from progressing to such complications.

Our Model/Product can be used by people for predicting if they have diabetes or not and for predicting if they have heart disease or not because

1. It has an increased accuracy for effective heart disease diagnosis as well as for diabetes.
2. Handles an enormous amount of data (using random forest algorithm and feature selection).
3. Saves a lot of time.
4. Cost-effective for users/patients.
5. Safest way for people to predict their disease is this pandemic because they don’t have to visit the hospital.

Challenges we ran into

We faced issues during the deployment using the Flask Framework which was particularly the library issue, rectified the same. We also faced challenges in the modeling part but later we used hyperparameter tuning in order to increase the overall accuracy of our model, there were certain issues regarding the deployment on certain platforms hence we deployed our model on localhost.