  Artificial intelligence (AI) will pave the way to a new era in medicine.
However, currently available AI systems do not interact with a patient, e.g.,
for anamnesis, and thus are only used by the physicians for predictions in
diagnosis or prognosis. However, these systems are widely used, e.g., in
diabetes or cancer prediction. In the current study, we developed an AI that is
able to interact with a patient (virtual doctor) by using a speech recognition
and speech synthesis system and thus can autonomously interact with the
patient, which is particularly important for, e.g., rural areas, where the
availability of primary medical care is strongly limited by low population
densities. As a proof-of-concept, the system is able to predict type 2 diabetes
mellitus (T2DM) based on non-invasive sensors and deep neural networks.
Moreover, the system provides an easy-to-interpret probability estimation for
T2DM for a given patient. Besides the development of the AI, we further
analyzed the acceptance of young people for AI in healthcare to estimate the
impact of such system in the future.

Computers and Society;Machine Learning;Machine Learning