MediMap AI

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  MediMap AI

Inspiration

Brain tumors are often diagnosed late, leading to severe health risks. We wanted to create a tool that empowers users with AI-driven insights, enabling early detection and better symptom tracking. Inspired by real-world challenges in medical diagnostics, we aimed to bridge the gap between technology and accessible healthcare.

What it does

MediMapAI is an AI-powered platform for MRI-based brain tumor detection, classification, and symptom tracking. Users can log symptoms, generate NLP-driven reports, and analyze MRI scans for potential tumors.

How we built it

We developed MediMapAI using Python, React, PyTorch, TensorFlow, and Keras. The AI pipeline was deployed via FastAPI on Hugging Face Spaces, while Firebase and Firestore handle user authentication and symptom tracking. OpenAI’s API powers the NLP-based reports, offering personalized insights for users.

Challenges we ran into

Processing medical images required extensive dataset preprocessing and fine-tuning AI models to achieve 99% accuracy. Integrating NLP for symptom analysis also posed challenges in structuring meaningful insights. Ensuring a seamless user experience while handling complex AI workflows was another hurdle.

Accomplishments that we're proud of

We successfully built a high-accuracy AI model for tumor detection and classification. Our multi-model AI pipeline enables robust analysis, while the symptom tracker provides valuable insights for early diagnosis. Combining image processing, NLP, and real-time user input, we created a comprehensive tool for both patients and doctors.

What we learned

We deepened our understanding of AI-driven medical diagnostics, optimizing machine learning models for real-world applications. Working with FastAPI, Firebase, and OpenAI's API improved our backend skills, while refining frontend development in React ensured usability.

What's next for MediMapAI

We plan to enhance MediMapAI by expanding support for detecting and analyzing more tumor types, improving its accuracy and usability for a wider range of medical conditions.

Video is on our YouTube channel: https://www.youtube.com/@MediMap-AI

Built With

• chart.js
• efficientnet
• fastapi
• firebase
• firestore
• flask
• github
• huggingface
• inceptionv3
• javascript
• kaggle
• keras
• matplotlib
• numpy
• openai
• pandas
• python
• pytorch
• react
• resnet50
• scikit-learn
• spacy
• tensorflow
• vercel
• vgg16