🚀 Transforming Medical AI Through Diversity 🌍
As a medical doctor and founder of Craniolabs, I’ve embarked on a mission to tackle a pressing issue in medical AI: the critical lack of diverse, high-quality imaging data from underrepresented regions like Africa, Asia, and the Middle East.
Key Insights:
- Target Problem: Bias in medical datasets remains largely unaddressed.
- Our Approach:
- Partnered with hospitals in Egypt and Dubai.
- Accessed and de-identified DICOM archives.
- Integrated NVIDIA MONAI for efficient annotation.
- Challenges Faced:
- Limited engagement from over 30 diagnostic AI startups despite the demand for better data.
- Identified that many startups are resource-strapped and hesitant to manage data logistics.
We’re now restructuring toward a subscription-based model to provide curated, compliant data solutions. 💡
Join the Conversation: Have you faced similar challenges in healthcare, AI, or infrastructure? Share your experiences and let’s learn together! 🤝
🔗 Explore more about our journey at Craniolabs.