MedGPT

Description

MedGPT is an AI-powered tool that provides fast and accurate second opinions for stroke and breast cancer identification. By analyzing brain scans and patient questionnaires, proposed framework ensures reliable validation of patient conditions. Introduced system give real-time evaluation of health issues with 24/7 mental health and rehab support. Presented system have Reminders section for sufferer to take timely appointments and medicine. State-of-the-art MRI-based stroke detection model leverages cutting-edge AI technology to accurately identify stroke indicators. System with Real time assessment of patient in user-friendly manner with 24/7 support. Framework that analyzes hybrid input of brain scans and patient questionnaires improving patient outcomes and precision. Ensuring rapid and reliable assessments to aid in critical care decisions.

Table of Contents

MedGPT

• Application Description
• Table of Contents
• Contributing
• Authors
• License

TRY the prototype

MedGPT

Technology Stack

Technology	Description
TensorFlow	Machine Learning Framework
Python	Programming Language
Flask	Web Framework
Docker	Containerization
Typescript	A programming language and core technology of the Web.
Next 14	Modern React Framework for Server Side Rendering Web Framework
Tailwind CSS	A utility-first CSS framework for rapidly building custom designs.
Supabase	Open Source Firebase Alternative for Authentication & Database.

Features

• Real-time Diagnostic Assistance: MedGPT analyzes brain scans and patient questionnaires to provide fast and accurate second opinions for stroke and cancer diagnoses.

• Focused on Stroke Detection: In its first phase, MedGPT specializes in stroke detection, ensuring rapid and reliable assessments critical for patient care.

• Future Expansion: MedGPT aims to expand its capabilities to include autonomous diagnoses for various medical conditions, advancing the speed and accuracy of medical diagnostics.

• Cross-platform Compatibility: MedGPT is designed to work across various platforms, including smartphones, tablets, computers, and medical imaging systems, ensuring accessibility in diverse healthcare environments.

Authors

Name	Link
Muhammad Talal Jamil	GitHub
Ehtisham Khan	GitHub
Areesa Ashfaq	GitHub
Sandra Ashipala	GitHub
Caner Akturk	GitHub

License