COPD Machine Learning Dataset

A collection of feature datasets derived from lung computed tomography (CT) images, which can be used in diagnosis of chronic obstructive pulmonary disease (COPD). The images in this database are weakly labeled, i.e. per image, a diagnosis(COPD or no COPD) is given, but it is not known which parts of the lungs are affected. Furthermore, the images were acquired at different sites and with different scanners. These problems are related to two learning scenarios in machine learning, namely multiple instance learning or weakly supervised learning, and transfer learning or domain adaptation. (Veronika Cheplygina, Isabel Pino Pena, Jesper Holst Pedersen, David A. Lynch, Lauge S., Marleen de Bruijne)