Value of Public Challenges for the Development of Pathology Deep Learning Algorithms
Douglas J. Hartman, Jeroen van der Laak, Metin N. Gürcan, Liron Pantanowitz
Abstract
The introduction of digital pathology is changing the practice of diagnostic anatomic pathology. Digital pathology offers numerous advantages over using a physical slide on a physical microscope, including more discriminative tools to render a more precise diagnostic report. The development of these tools is being facilitated by public challenges related to specific diagnostic tasks within anatomic pathology. To date, 24 public challenges related to pathology tasks have been published. This article discusses these public challenges and briefly reviews the underlying characteristics of public challenges and why they are helpful to the development of digital tools.
Topics & Concepts
Digital pathologyComputer scienceDiscriminative modelData sciencePathologyMedicineArtificial intelligenceAI in cancer detectionDigital Imaging for Blood DiseasesCell Image Analysis Techniques