The INMP at the National University of Tainan (Taiwan)
The results of the research project ODINO (Ontological DIsease kNOwledge), carried out in the framework of the scientific cooperation between the NIHMP and CORISA (University of Salerno), which is collaborating with the University of Tainan, have been presented at the National University of Tainan (Taiwan) on 25 June 2010. The meeting was presided over by Hsiu-Shuang Huang (Chancellor of the National University of Tainan), Chang-Shing Lee (Full Professor at the National University of Tainan), Vincenzo Loia (Director of Corisa) and the III Research Group.
The project ODINO studies the application of semantic modelling techniques to medical information and advanced languages to represent logical relations between conceptions belonging to the same context. The main objective of the project is to realise a medical diagnosis support system originating from a new model of pathology based on fuzzy logic, to represent the disease through ontologies (decision support system ontology driven) and to provide medical second opinion. The existing formal models for representing medical information has hampered the creation of medical diagnosis support systems. The innovative studies carried out by the NIHMP, based on the semantics of medical information and on its logical deductive analysis, allow to produce new ideas and knowledge about the diagnosis of diseases such as diabetes, leprosy, AIDS, tuberculosis and malaria starting from correlated semantic entities, namely symptoms/signs, complications, clinical tests and treatment protocols. The developed model attracted the attention of several universities in the world, namely the CORISO (Italy), the Nanjing University (China) and other research centres in Great Britain, Canada and Japan. It was proposed an agreement between the NIHMP and some international research centres in order to realise a useful semantic portal based on the Rich Internet Application (RIA) and providing the following functions:
• An ontological reasoning engine allowing to classify pathologies and based on the knowledge model and the correlation meta-model <pathologies, (symptoms/signs, complications, clinical tests)>;
• An advanced research, allowing to identify those pathologies that can be related with the collected data. The systems shows the results together with a priority index considering the correlation degree existing between symptoms/signs, complications and pathologies;
• Hypertext and taxonomy navigation, allowing health professionals to navigate between the identified pathologies in order to study their characteristics (semeiotics, complications, images, clinical tests and treatment protocols).
The Nanjing University and the III Research Group invited the Institute to cooperate for a research path aimed at applying the model proposed by the NIHMP.