---
title: Onsite Health Diagnostic
emoji: 💻
colorFrom: purple
colorTo: red
sdk: streamlit
sdk_version: 1.32.2
app_file: app.py
pinned: false
license: mit
---


# Onsite-Health-Diagnostic (OHD)
Onsite Health Diagnostic (OHD) is the web application that allows users to predict whether the user has been infected with a menacing disease or not. These diseases can be very dangerous to health if they are not treated properly. The main objective of OHD is to help people predict the disease in case of absence of medical professionals, strikes or any related uncertainties.

## Website
link:

## Table Of Contents

-   [Datasets](#Datasets)
-   [Clone](#Clone)
-   [Licence](#Licence)


## Datasets
 - Pneumonia            :              [Dataset](https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia)
 - Brain tumour         :              [Dataset](https://www.kaggle.com/ahmedhamada0/brain-tumor-detection)
 - Diabetes             :              [Dataset](https://github.com/praj2408/Onsite-Health-Diagnostics/blob/main/src/Diabetes-Detection/diabetes.csv)
 - Heart disease        :              [Dataset](https://github.com/praj2408/Onsite-Health-Diagnostics/blob/main/src/Heart-Disease/heart.csv)
 - Breast Cancer        :              [Dataset](https://github.com/praj2408/Onsite-Health-Diagnostics/blob/main/src/Breast%20Cancer/data.csv)
 - Malaria-Detection    :              - [Dataset](https://lhncbc.nlm.nih.gov/LHC-publications/pubs/MalariaDatasets.html#:~:text=Abstract%3A,the%20Malaria%20Screener%20research%20activity.&text=The%20dataset%20contains%20a%20total,of%20parasitized%20and%20uninfected%20cells.)


## Clone

1. Clone the repository:
```
git clone https://github.com/praj2408/Onsite-Health-Diagnostics
```
2. Install dependencies
```
pip install -r requirements.txt
```
3. Run the application
```
streamlit run app.py
```


## License
This project is licensed under the MIT License - see the LICENSE file for details.