Receptivity of an AI Cognitive Assistant by the Radiology Community: A
  Report on Data Collected at RSNA
  Due to advances in machine learning and artificial intelligence (AI), a new
role is emerging for machines as intelligent assistants to radiologists in
their clinical workflows. But what systematic clinical thought processes are
these machines using? Are they similar enough to those of radiologists to be
trusted as assistants? A live demonstration of such a technology was conducted
at the 2016 Scientific Assembly and Annual Meeting of the Radiological Society
of North America (RSNA). The demonstration was presented in the form of a
question-answering system that took a radiology multiple choice question and a
medical image as inputs. The AI system then demonstrated a cognitive workflow,
involving text analysis, image analysis, and reasoning, to process the question
and generate the most probable answer. A post demonstration survey was made
available to the participants who experienced the demo and tested the question
answering system. Of the reported 54,037 meeting registrants, 2,927 visited the
demonstration booth, 1,991 experienced the demo, and 1,025 completed a
post-demonstration survey. In this paper, the methodology of the survey is
shown and a summary of its results are presented. The results of the survey
show a very high level of receptiveness to cognitive computing technology and
artificial intelligence among radiologists.
