The virtual doctor: An interactive clinical-decision-support system based on deep learning for non-invasive prediction of diabetes.

Clicks: 439
ID: 60937
2019
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Abstract
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 a system in the future.
Reference Key
spnig2019theartificial Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Spänig, Sebastian;Emberger-Klein, Agnes;Sowa, Jan-Peter;Canbay, Ali;Menrad, Klaus;Heider, Dominik;
Journal artificial intelligence in medicine
Year 2019
DOI
S0933-3657(19)30108-3
URL
Keywords
Deep learning artificial intelligence Machine learning Diabetes e-health diagnostics

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