Polypathology Diagnosis Platform

Deploying web app for multiple disease prediction
Webapp Link: PolyDiag-Platform

Project Objective:

The Polypathology Diagnosis Platform includes prediction models for diabetes, heart disease, and Parkinson's disease.

1. Prediction Model of Diabetes: Develop a machine learning model that can accurately predict the likelihood of an individual developing diabetes based on demographic, lifestyle, and medical factors. The goal is to improve the accuracy and efficiency of diabetes prediction and ultimately improve patient outcomes.
2. Prediction Model of Heart Disease: Develop a machine learning model that can accurately predict the likelihood of an individual developing heart disease based on demographic, lifestyle, and medical factors. The goal is to improve the accuracy and efficiency of heart disease prediction and ultimately improve patient outcomes.
3. Detection Model of Parkinson's Disease: Develop a high accuracy and efficient machine learning model to predict the likelihood of an individual developing Parkinson's disease by considering demographic, lifestyle, and medical factors. The goal is to provide an improved and more accurate prediction of Parkinson's disease, leading to earlier diagnosis and better patient outcomes.

Data Collection:

1. The Diabetes Detection Model is trained using the Diabetes Dataset, which is sourced from Kaggle. The attribute information of this dataset can be found here.
2. The Heart Disease Detection Model is trained using the Heart Disease Dataset, which is sourced from Kaggle. The attribute information of this dataset can be found here.
3. The Parkinson's Disease Detection Model is trained using the Parkinson's Data Set, which is obtained from Kaggle. The attribute information of this dataset can be found here.