Heart Disease Prediction Android App

Abstract / Introduction
Heart disease is one of the leading causes of death worldwide. Early detection and monitoring can significantly reduce the risk and help individuals take preventive measures. However, many people do not have easy access to quick health risk assessment tools. The proposed Android-based Heart Disease Prediction System uses machine learning techniques to analyze user health parameters and predict 
the likelihood of heart disease. The user enters medical information such as age, blood pressure, cholesterol level, and heart rate through a mobile application. A trained machine learning model processes the data and provides a prediction result indicating whether the person has a low or high risk of heart disease. This application can help users monitor their health condition and seek medical advice at an early stage.
 

Functional Requirements
1. FR1: The system shall allow users to enter personal health information such as age, gender, blood pressure, and cholesterol level. 

2. FR2: The system shall process the entered health data using a trained machine learning model. 

3. FR3: The system shall predict the risk level of heart disease based on the input parameters. 

4. FR4: The system shall display prediction results to the user in an easy-to understand format. 

5. FR5: The system shall provide basic health recommendations based on prediction results. 

6. FR6: The system shall allow users to view their previous prediction history. 

7. FR7: The system shall ensure user-friendly interaction through a simple Android interface. 

8. FR8: The system shall store prediction data for future reference.