priyanshu2026 / heart-disease

it is a Prediction model to predict Heart attack or symptoms and with basic UI

Heart-disease

it is a Prediction model to predict Heart attack or symptoms and with basic UI

Here's a sample README.md file for your Git repository, describing the purpose and usage of your medical prediction code:

# Medical Prediction System

This repository contains code for a medical prediction system that predicts the severity of a medical condition based on patient data. The system is built using machine learning techniques and is intended to assist healthcare professionals in making informed decisions.

## Features

- Predicts the severity of a medical condition based on patient data.
- Supports various input features such as age, sex, chest pain type, fever, cough, shortness of breath, chest pain, and fatigue.
- Provides a user-friendly interface for entering patient data and viewing predictions.

## Installation

2. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the application:

   python app.py

2. Enter the required patient data in the provided fields.
3. Click the "Predict" button to view the predicted severity of the medical condition.

Data

The training data used for the machine learning model is not included in this repository. You can use your own dataset or obtain a suitable dataset from sources such as the UCI Machine Learning Repository.

Credits

This project was developed by [PRIYANSHU TIWARI AND DHANANJAY KUMAR] as part of [Heart-disease Prediction].

License

This project is licensed under the [SIR M VISVVESVARAYA INSTITUTE OF TECHNOLOGY] License - see the LICENSE file for details.

Replace `[PRIYANSHU TIWARI AND DHANANJAY KUMAR]`, `[Heart-disease Prediction]`, and `[License ]` with your actual name, project name, and license name, respectively. You can choose an appropriate open-source license for your project.

heart-disease's Issues

hey priyanshu i can make a cancer cell prediction model

i can make a ml model based on thyroid prediction with more than 85 percent of accuracy.