EMMI Enquiry Model for Medical Investigation

In recent years, artificial intelligence technologies were introduced in medicine as a support to the diagnostic process. Among others, the multi-systemic and multi-factorial disorders, that involve different aspects of human anatomy and could be triggered by many factors, genetic and environmental, became a challenging application field for AI. The analysis of those factors, in fact, requires the integration of heterogeneous information coming from different fields (genome screening, neuroimaging, environmental risk factors, etc.). The support of artificial intelligence technologies becomes crucial for a better understanding of this kind of diseases, not only for the identification of the factors but also to explain how these factors can impact on the disease. In this paper we present EMMI (Enquiry Model for Medical Investigation): an ontology-driven automatic medical inquirer that (in a first application context), leveraging an Interrogative Model of Inquiry, is able to selectively extract information from different sources in order to infer explanations about relationships between different aspects impacting on Autism Spectrum Disorder etiology.