Harmonization of conflicting medical opinions using argumentation
  protocols and textual entailment - a case study on Parkinson disease
  Parkinson's disease is the second most common neurodegenerative disease,
affecting more than 1.2 million people in Europe. Medications are available for
the management of its symptoms, but the exact cause of the disease is unknown
and there is currently no cure on the market. To better understand the
relations between new findings and current medical knowledge, we need tools
able to analyse published medical papers based on natural language processing
and tools capable to identify various relationships of new findings with the
current medical knowledge. Our work aims to fill the above technological gap.
  To identify conflicting information in medical documents, we enact textual
entailment technology. To encapsulate existing medical knowledge, we rely on
ontologies. To connect the formal axioms in ontologies with natural text in
medical articles, we exploit ontology verbalisation techniques. To assess the
level of disagreement between human agents with respect to a medical issue, we
rely on fuzzy aggregation. To harmonize this disagreement, we design mediation
protocols within a multi-agent framework.
