Local Chapter Challenge
Applying Computer Vision for Red Blood Cell Classification to Diagnose Sickle Cell Disease
Challenge Completed!
This Omdena Local Chapter Challenge runs for 5 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.
You will work on solving a local problem, initiated by the Omdena Benin Chapter.
The problem
Obtaining certain medical diagnoses can be difficult for people living in developing countries due to their populations. In particular, for rural people, sickle cell anemia or even sickle cell traits are not diagnosed in time because of the remoteness of appropriate medical centers and laboratories and the cost of electrophoresis tests.
The goals
The goals of this project are:
- Collate and label blood cell datasets for sickle cell anemia.
- Build and train a model to detect sickled cells in blood cell images.
First Omdena Local Chapter Challenge?
- Beginner-friendly, but also welcomes experts
- Education-focused
- Open-source
- Duration: 4 to 8 weeks
Your Benefits
- Address a significant real-world problem with your skills
- Build your project portfolio
- Access paid projects (as an Omdena Top Talent)
- Get hired at top organizations
Requirements
- Good English
- Suitable for AI/ Data Science beginners but also more senior collaborators
- Learning mindset
