Congestive Heart Failure Prediction

This paper presents a web application based on a machine learning (ML) algorithm that helps users predict the chance of Congestive Heart Failure (CHF) and analyze their mental health using a set of questions and answers. The application utilizes a SQLite database with five tables, including Patient, Doctor, Lab_assistant, Appointments, and Test Result, to store and manage relevant data. The ML algorithm is trained on a large dataset of clinical data from these tables, including patient demographics, medical history, and relevant risk factors. The web application provides accurate predictions of CHF risk and valuable insights into the user’s mental health, contributing to improved healthcare outcomes..