Detecting Pediatric Acute Lymphoblastic Leukemia using Computer Vision
Challenge Background
In ALL there is an accumulation in the bone marrow of immature lymphocyte precursor cells, called blast cells. Eventually, the production of normal blood cells is affected by this, resulting in a reduction in the number of red cells, normal white cells, and platelets in the blood.
ALL is the only form of leukemia that is more common in children than adults. It is the single most common form of pediatric cancer, accounting for about one-third of all cases in children. About 85% of cases of childhood leukemia are ALL and it occurs in about 400 children in the UK each year. ALL occurs mostly between the ages of about two and four years. Males are affected more often than females at all ages.
Project Timeline
Week 1: Data collection / organisation
Week 2: Data cleaning / augmentation / engineering
Explore the images and any augmentations with analysis
Build and test a computer vision model
Develop an app for inference
test
What you'll learn
Data collecting / organisation, Data cleaning / augmentation / engineering, Exploratory Analysis, Building a Computer Vision model, Develop and deploy an app.
First Omdena Local Chapter Project?
Beginner-friendly, but also welcomes experts
Education-focused
Duration: 4 to 8 weeks
Open-source
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
Application Form
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