#Team Members

• Ikram Tauffiqul H
• Mahendra Adi R
• Novita Risdanti

#Project Overview

Mediscan was developed as part of the Compfest AI Innovation Challenge, focusing on leveraging technology to improve healthcare services. Our app addresses the challenges of doctor handwriting recognition and drug identification through innovative machine learning techniques.

#Key Features:

#1. Doctor Handwriting Recognition

Utilizing YOLOv5, Mediscan trains a model to recognize real-world doctor handwriting, enabling accurate interpretation of prescriptions.

#2. Drug Identification

Mediscan's second feature involves detecting and identifying drugs from their cover, providing users with detailed information about each drug.

#3. Pharmacy Locator

Users can conveniently locate nearby pharmacies through Mediscan's integrated feature, facilitating easy access to medications.

#Technical Details:

#Drug Data Scraping

Python scripts with BeautifulSoup are used to scrape drug information from the K24Klik website, allowing for comprehensive drug information.

#Deployment

The entire application is containerized using Docker and deployed on Google Cloud Platform (GCP)