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Parkinson's disease is the second most common neurodegenerative disease,affecting more than 1.2 million people in Europe. Medications are available forthe management of its symptoms, but the exact cause of the disease is unknownand there is currently no cure on the market. To better understand therelations between new findings and current medical knowledge, we need toolsable to analyse published medical papers based on natural language processingand tools capable to identify various relationships of new findings with thecurrent medical knowledge. Our work aims to fill the above technological gap.  To identify conflicting information in medical documents, we enact textualentailment technology. To encapsulate existing medical knowledge, we rely onontologies. To connect the formal axioms in ontologies with natural text inmedical articles, we exploit ontology verbalisation techniques. To assess thelevel of disagreement between human agents with respect to a medical issue, werely on fuzzy aggregation. To harmonize this disagreement, we design mediationprotocols within a multi-agent framework.

Harmonization of conflicting medical opinions using argumentation protocols and textual entailment - a case study on Parkinson disease