Symptom Checker is a basic web-based tool built with Streamlit that enables users to quickly predict minor illnesses based on their selected symptoms. The application leverages a Decision Tree Classifier to provide an initial diagnosis, allowing users to gain insights into potential health issues. This tool is a demo for a quick self-check.

Check out the live Streamlit App here.

• User-friendly Interface: Easily select symptoms from a list to get a prediction.
• Accurate Condition Prediction: Utilizes a trained Decision Tree Classifier model.
• Drug Information: Displays related drug options for the predicted condition, sourced from a drug side effects dataset.
• Responsive Design: Accessible from any device, whether on mobile or desktop.
• Error Handling: Ensures users select symptoms before making a prediction.

1. Clone this repository:

   git clone https://github.com/kimnguyen2002/Symptoms_Checker.git
   cd Symptoms_Checker

2. Install the required packages:

pip install -r requirements.txt

3. Download the symptoms_dataset.csv and drugs_side_effects.csv files. Place these files in the project directory.

Start the Streamlit application by running:

streamlit run symptoms_checker.py

Feel free to adjust the structure to fit your actual project layout!