Bell Eapen

eHealth and Information System Research

Importing ONTODerm Ontology

Map of Colombia with Departments
Map of Colombia with Departments (Photo credit: Wikipedia)

Two engineering students from Colombia are using ONTODerm for a noble cause. They are planning to take dermatology to the poor and the underprivileged. They started a teledermatology project, but discontinued it because of lack of support. Now they are working on an Ontology based diagnostic application using semantic web technologies.

One of the problems they have encountered may be important to be addressed here. They could not import ONTODerm into Sesame. The URL provided in the ONTODerm home page is protege specific. However you can export the latest ONTODerm version in the native format from the project page on knoodl. Just request for a free membership to ONTODerm community.

Please keep me posted if you are using ONTODerm or DermKnowledgeBASE for any such projects and I wish both of them all the very best.

DermKnowledgeBASE – A Dermatology Knowledge Base with semi-automated knowledge discovery.

English: Map Summarizing Rosacea, It was creat...
English: Map Summarizing Rosacea, It was created by the author and Reem Al-Qudah using Clinical dermatology book Dahl, Mark V.; Weller, Richard E.; Hunter, John G.; Savin, John (2008). Clinical Dermatology. Wiley-Blackwell. Reference (Photo credit: Wikipedia)

For the last few weeks I have been working on DermKnowledgeBASE (DKB) that I believe is the first RDF knowledgebase for dermatology. It implements RDFS using RAP library for php. The terminology in dermatology facilitate the diagnostic process because many skin disorders have distinct features that can be represented by appropriate categories of terms. But dermatological terms are different from the traditional medical linguistics. Hence DKB is not rooted on MeSH  or any popular medical ontologies but on ONTODerm, the ontology I started developing for dermatology. I wrote about an offshoot of this project called slise before. DKB makes use of eutil webservices and whatizit from EBI. It is semi automated and can learn most of the relations on its own. But it relies on curators for confirming difficult rules. Its focus is on providing diagnostic support. Hence curators can add further information about the relevance of each feature in a particular disease. Features can be classified as pathognomonic, common, important, rare etc which helps in streamlining diagnostic accuracy. It provides a range of  functions and SOAP web services in addition to a ‘consult’ function to obtain differential diagnosis based on the description of clinical findings. It is still early days, but hopefully it may evolve into a very useful application for dermatology.

Click the banner below to access DermKnowledgeBASE: