AI Foundations for Oncology

Hands-on course applying 15 small, local AI models to oncology use cases

Overview

A comprehensive hands-on course focused on applying AI models to oncology use cases, with emphasis on practical implementation using local, small-scale models.

Course Highlights

  • 15 AI Models: Explored and implemented 15 different AI models for oncology applications
  • Local Deployment: Focus on small, locally-deployable models suitable for clinical settings
  • Practical Applications: Real-world oncology use cases including image analysis, text mining, and prediction tasks

Topics Covered

  • Medical image analysis and classification
  • Text mining from clinical notes
  • Drug response prediction
  • Patient outcome modeling
  • LLM applications in oncology

Technologies Used

  • LLM Frameworks: Ollama, HuggingFace
  • ML Libraries: PyTorch, Scikit-learn
  • Specialized: MONAI for medical imaging
  • RAG: Retrieval-Augmented Generation for clinical Q&A

Certification

✅ Certified: AI Foundations for Oncology (December 2025)

Key Takeaways

  • Understanding of AI applications specific to cancer research
  • Hands-on experience with model deployment in resource-constrained environments
  • Knowledge of ethical considerations in medical AI