The problem MediBuddy solves

Medibuddy is an integrated solution designed to streamline medical data access and utilization for healthcare professionals. By harnessing the power of Optical Character Recognition (OCR) and Natural Language Processing (NLP), MedScanOCR delivers accurate, structured, and easily searchable patient data from diagnostic reports. OCR powered: Effortlessly extract text from medical images and PDFs, eliminating manual data entry.
Key features:

1. Image/PDF to text (OCR): App Capable to converting images and pdfs to texts seamlessly and accurately using OCR mechanism
2. User friendly interface: MediBuddy provides a user friendly interface so as to ensure best results in the easiest way possible
3. Chatbot: A Custom Fine Tuned LLM available at the doctors disposal where the doctor can upload the patients report and interact with the chatbot
4. Upload medical report: Our application allows the user(patient) to upload their medical reports for the doctor to analyze them and provide required medication
5. Real time chat: Allows the doctor and patient to chat with each other to gaurantee patient satisfaction and allow 24/7 emergency assistance from the doctors end
6. Advice: Recommends fitness exercises to maintain patients health based on patients body type
7. Two interfaces: App lets users create profiles and select the roles of doctor or patient , dynamically displaying different features in the app based on the role
8. Pharmacy: The application has an inbuilt pharmacy from where they get fast access to medicines prescribed by doctors

Challenges we ran into

We ran into multiple hurdles while building this project. Some of the problems we faced were:

1. Version conflict: Different libraries support different python versions, we overcame this by reading documnentations of these libraries and in some cases we used conda (version independent) and other methods.
2. Integration: It was a tedious task to integrate our python models to the flutter application. We overcame this by using flask and firebase for storing the data.