Towards a Deeper Understanding of How a Pathologist Makes a Diagnosis: Visualization of the Diagnostic Process in Histopathology
Birgit Pohn, Michaela Kargl, Robert Reihs, Andreas Holzinger, Kurt Zatloukal, Heimo Müller · 2019
Advancements in Artificial Intelligence (AI) and Machine Learning (ML) are enabling new diagnostic capabilities. In this paper we argue that the very first step before introducing AI/ML into diagnostic workflows is a deep understanding of how pathologists work. To contribute to a deeper understanding of the diagnostic process in histopathology, we developed a visualization concept, including: (a) the sequence of the views observed by the pathologist (Observation Path), (b) the sequence of the spoken comments and statements of the pathologist (Dictation Path), (c) the underlying knowledge and experience of the pathologist (Knowledge Path), (d) information about the current phase of the diagnostic process and (e) the current magnification factor of the microscope chosen by the pathologist. We implemented the proofof-concept prototype as HTML5/CSS3/JavaScript application.