KDD Cup 2006: Pulmonary embolisms detection from image data

This year's KDD Cup challenge problem is drawn from the domain of medical data mining. The tasks are a series of Computer-Aided Detection problems revolving around the clinical problem of identifying pulmonary embolisms from three-dimensional computed tomography data. This challenging domain is characterized by:

  • Multiple instance learning
  • Non-IID examples
  • Nonlinear cost functions
  • Skewed class distributions
  • Noisy class labels
  • Sparse data

Download the Gzipped tarball for scoring scripts, test data, raw results, Final PDF rules file, bootstrap vectors, etc.

Copyrights © 2023 All Rights Reserved - SIGKDD
ACM Code of Conduct