Bell Eapen

Physician | HealthIT Developer | Digital Health Consultant

Testing Webservices

Debugging (Photo credit: mikemol)

Last night I added 2 more webservices to DermKnowledgeBASE. Debugging webservices is a nightmare. (At least it was, until the wee hours of the morning). It always returns SoapFault exception mentioning that “looks like we got no XML document”. After several wasted hours of hard work I found the way to use the instruction here. The best answer is rather cryptic. So I have included the code I used to display the request and response so that debugging becomes much easier.

Change the wsdl path and the function call. Hope this saves some time for someone!

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.

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