Step-by-step guides to master medical AI development on AfriBiobank
Create account, navigate the platform, and access your first dataset
Learn about DICOM, NIfTI, and other medical imaging formats
Navigate, annotate, and export medical images
Train a chest X-ray classifier using PyTorch and AfriBiobank data
Train models across multiple institutions without sharing data
Clean, normalize, and augment medical imaging data
Fine-tune existing models for your specific use case
Combine X-rays, CT scans, and clinical data in one model
MLOps, containerization, and real-time inference
Grad-CAM, attention maps, and model interpretability
Case study: Building a production TB classifier
U-Net and 3D CNNs for medical image segmentation
Using AfriBiobank for patient cohort identification
Structured courses for different roles
For PhDs and postdocs new to medical AI
For AI developers building products
For MDs and clinical investigators
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