Android Heart Disease Prediction App

Android Heart Disease Prediction App

Abstract:

Heart disease kills millions worldwide. Early heart disease detection improves treatment and survival. This article introduces a cardiovascular health and heart disease prediction Android app. The app predicts cardiovascular diseases based on age, gender, blood sugar, cholesterol, and blood pressure. The app also lets users search for doctors by specialty. This article covers the app’s features, including the admin and user roles and the Random Forest prediction algorithm.

Introduction:

Heart disease kills countless people worldwide. Early heart disease detection improves treatment and survival rates. An Android app that assesses cardiovascular health and predicts heart disease was created to meet this need. The app analyzes age, gender, blood sugar, cholesterol, and blood pressure to assess heart health.

Objectives:

The Android Heart Disease Prediction App helps users assess their cardiovascular health and predict heart disease. The app uses user data and Random Forest to make accurate predictions. The app also provides a comprehensive doctor directory to help users find specialists for their healthcare needs.

Project Details:

The Android Heart Disease Prediction App has several key features to make it user-friendly and informative. User and admin roles make up the app.

Title: Android Heart Disease Prediction App

Abstract: Heart disease is a leading cause of mortality worldwide, claiming millions of lives annually. Early detection of heart disease is crucial for effective treatment and improved survival rates. This article introduces an Android app specifically developed for predicting heart disease and assessing cardiovascular health. By considering various factors such as age, gender, blood sugar, cholesterol levels, and blood pressure, the app generates predictions about potential cardiovascular ailments. Additionally, the app provides a directory of doctors, allowing users to search for specialists based on their medical needs. This article discusses the features and functionality of the app, including the role of the admin and the user, as well as the implementation of the Random Forest algorithm for prediction.

Introduction: Heart disease poses a significant health challenge globally, responsible for a staggering number of deaths each year. The ability to detect heart disease at an early stage can greatly improve the chances of successful treatment and enhanced survival rates. Recognizing this critical need, an Android app has been developed to help users assess their cardiovascular health and predict potential heart diseases. By analyzing key factors such as age, gender, blood sugar, cholesterol levels, and blood pressure, the app aims to provide valuable insights into an individual’s heart health.

Objective: The main objective of the Android Heart Disease Prediction App is to empower users with the ability to assess their cardiovascular health and obtain predictions about potential heart diseases. By leveraging user-provided data and employing the Random Forest algorithm, the app aims to deliver accurate and reliable predictions. Furthermore, the app seeks to facilitate access to medical professionals by offering a comprehensive directory of doctors, allowing users to find specialists based on their specific healthcare needs.

Project Details: The Android Heart Disease Prediction App encompasses several key features and functionalities to ensure a user-friendly and informative experience. The app consists of two main user roles: the admin and the user.

1. Admin:
   • The admin is responsible for managing the training data, enabling the system to adapt and improve its prediction capabilities.
   • The admin has the authority to update and modify values within the app, ensuring the accuracy and relevance of the prediction process.
   • Additionally, the admin oversees the management of doctors and their clinic details, allowing for an up-to-date directory of healthcare providers.
   • The admin can access user profiles and review their feedback, enabling continuous app enhancements based on user suggestions.
2. User:
   • To access the prediction services, users are required to create an account within the app.
   • Users need to provide 13 specific data points, including age, gender, blood sugar, cholesterol levels, and blood pressure, for the prediction process.
   • The Random Forest algorithm, implemented using Asp.net with C#, analyzes the user-provided data to generate predictions about potential heart diseases.
   • Users have the ability to update their profiles and change their passwords, ensuring a personalized and secure experience.
   • The app offers a user-friendly interface for navigating through the prediction process and accessing the directory of doctors.
   • Users can search for doctors based on their specialty, facilitating the identification of appropriate healthcare professionals.

Conclusion:

The Android Heart Disease Prediction App helps cardiovascular health-conscious people. The app predicts heart diseases using user data and the Random Forest algorithm. The app’s doctor directory helps users find local specialists. Early heart disease detection improves treatment and survival. This app empowers users to maintain heart health and seek medical help with its user-friendly interface and robust features.

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