Sharing Web Clinical Knowledge Between Medical ...

Anais do XXVI Congresso da SBC SEMISH l XXXIII Seminário Integrado de Software e Hardware

14 a 20 de julho de 2006 Campo Grande, MS

Sharing Web Clinical Knowledge Between Medical Community to Support a Second Opinion Diagnosis D.F. Pires1 3 , R.A.I Halack2 , E.E.S. Ruiz3 1

Departamento de Ciência da Computaça˜ o – UniCOC Ribeirão Preto – SP – Brazil 2

SH Clinicas Ribeirão Preto – SP – Brazil 3

Departamento de F´ısica e Matemática – FFCLRP – USP Ribeirão Preto – SP – Brazil

[email protected], [email protected],[email protected]

Abstract. The exchange of clinical information among medical systems is an important feature to improve healthcare systems with novel clinical activities, such as to obtain a second opinion diagnosis from different physicians even in when their are not available at the requested time. However, technical and semantic interoperability problems must be explored to make these new activities possible. This works aims to discuss these problems and proposes solutions with Web services and UDDI to solve technical compatibility, and UMLS and Semantic Web are also proposed to address semantic challenges. SODOnt ontology, RDF documents, and Web services are proposed to create a protocol to support a second opinion diagnosis in a shared, service oriented, and distributed computer environment. An acute abdominal pain use case is also discussed.

1. Introduction In recent years, the exchange of clinical information among medical information systems has become a major research focus and an important feature for the healthcare system [Beyer et al. 2004, Joubert et al. 2004, Müller et al. 2005]. Perceived applications areas such as Electronic HealthCare System (EHS), Telemedicine and Decision Support Systems take advantages from the exchange of relevant information. Moreover, some new relevant situations may appear to users from similar applications, like the possibility of a second opinion diagnosis, or the exchange of electronic patient record (EPR) among hospital information systems (HIS). Specifically, in a scenario of a specialist second opinion diagnosis, the Web-based communication tools usage such as instant messenger, video-conference or a chat room can support clinical remote activities [Ho et al. 2004, Demiris 2003]. This way, physicians and students may discuss symptoms, signals and diagnosis values through an information exchange system; in other words, they can express a second opinion, which only occurs when they are online at the same time. To support a second opinion diagnosis, a knowledge base can be created based on learning machine techniques applied to a shared database. This way, it is possible to share knowledge clinical bases, for example, a physician or a medical student may have a second opinion from a specialist even he/she is off-line [Pires et al. 2005].

361

In order to exchange clinical knowledge among medical community to support second opinion diagnosis via Web, two interesting interoperability problems must be explored. The first is the technical interoperability problem, which happens when two or more computer applications running on heterogeneous computer architecture needs to share information. The second one is the semantic interoperability problem, which occurs when medical applications uses different medical terminology systems and/or incompatible ontology. The technical interoperability problem can be solved with Web services [Stal 2002], a W3C (World Wide Web Consortium) recommended specification, and UDDI (Universal Description, Discovery, and Integration) [Uddi 2006], a protocol specification required for successful Web services. The semantic interoperability problem can be explored with UMLS (Unified Medical Language System) [McCray and Nelson 1995], a knowledge source from of the U.S. National Library of Medicine, and with Semantic Web [Berners-Lee et al. 2001], a framework led by W3C to put machine-understandable data on the Web. Specifically, ontological and terminological compatibility, type level and instance level semantics problems respectively, are considered at this work. Syntactical compatibility is also solved, but is not discussed because it is considered that all exchanged and reused document clinical data are represented using XML (Extensible MarkUp Language). In this context, this work proposes to investigate and discuss technical and semantic interoperability challenges during the exchange and share of clinical knowledge among medical community under a second opinion diagnosis context. A service-oriented architecture, a method to publish and to discover the network-based software components, the UMLS knowledge source and Semantic Web Health Care are discussed and used to solve interoperability problems. To reach this purpose, a case study component-based software was developed based on acute abdominal pain pathology knowledge base. It is proposed a set of Web services - CKCWs, SODWs, CKPWs, CKDWs - to support second opinion diagnosis activities. A new ontology named SODont and RDF documents are also suggested and used to exchange and share information between physicians, a supposed specialist discussion board on the Web is also regarded as a possible integrated feature in this web system. This paper is organized as follows: next session presents some interesting related works and used standards. In Section 3 are discussed some clinical knowledge sharing approaches and reused benefits to medical community. Sections 4 and 5 discuss technical and semantic interoperability problems, respectively, and propose a solution to them. An acute abdominal pain use case is implemented and it is demonstrated in Section 6. In section 7, there is a discussion based on the results. Finally, future works are also suggested.

2. Used Standards and Related Works UMLS, Semantic Web, Web Services and UDDI specifications have been shown as important computer resources to solve the exchange of Web clinical knowledge considering the possible syntatic and semantic interoperability problems. This section briefly explains these standards and discusses some scientific efforts with successful applications of these standards.

362

A Web services activity [Booth et al. 2006] aims to promote and facilitate communication between two or more computer applications developed using different programming language and/or different computer architecture. To improve technical interoperability among web applications, this specification uses some technologies, such as: WSDL (Web Service Description Language) [Chinnici et al. 2006] to describe services interfaces using XML language, SOAP (Simple Object Access Protocol) [Mitra 2006] to format XML messages and to call remote object using HTTP, and UDDI, a standardsbased mechanism which classifies, catalogs, and manages Web services using tModels data structure, so that they can be used to discover and to be discovered by other computer applications. An usual scenario of UDDI usage, similar to the one applied at this work, would be like: a physician discussion board create a set of symptoms and diagnosis, and define a WSDL document that is registered in UDDI like a tModel. Specialist physician discover for this tModel, implement it, and register the implementation at UDDI. After that, a beginner physician look for tModel implementation and can make use appropriate Web services. Aloisio and co-authors [Aloisio et al. 2003] apply this kind of scenario to create a Web service architecture named TACWeb to support acquisition, processing and delivering biomedical data and images. UMLS [Umls 2006] aims to facilitate the share and reuse of information from multiple biomedical sources, by creating a repository of concepts and a semantic network that relates terms from thousands of terminology systems. The UMLS is basically composed of tree systems: the UMLS Metathesaurus, the UMLS Semantic Network, and a SPECIALIST lexicon and Lexical Programs. The first is a set of health and biomedical related concepts, there are many terms, strings, and the relationships among them. The second system is a classification of all concepts presented in the UMLS Metathesaurus, furnishing information about the collection of semantic types which are associated to these concepts; and the last one is a general English lexicon that includes various health and biomedical related terms needed for the Natural Language Processing System specialist (Lexical Program). The researched literature shows some efforts to provide homogeneous access to biomedical data. The aim of CoMeDIAS (Computerized Medical Data through Internet Access Services) project [Joubert et al. 1998] is to propose a computer plataform to be used for current software tools, based on terminology standards (CIM-10 and SNOMED). It also intends to provide physicians a homogeneous way to access data, information and knowledge in a computer heterogeneous environment. Based on this project, Joubert and co-workers [Joubert et al. 2004] discuss heterogeneous health databases interoperability problems and present how to implement a system according to the CoMeDIAS principles. The implementation is component-based, uses UMLS knowledge sources, XML, and Web services. Beyer and colleagues [Beyer et al. 2004] assert that tree different compatibility aspects need to be considerated to discuss problems during exchanging and reusing clinical information among heterogeneous system: syntactical, ontological, and terminological. Syntactical compatibility is related to different encoding rules to represent data, XML and XML Schema are the best suited to solve these problems. Ontological compatibility is related to semantic heterogeneity on a type level and might result in incompatible database schemas. The resulted problems may be reduced if different vendors agree on

363

common ontology. HL7 ontology is well suited in hospital settings. The last one, terminological compatibility is related to semantic heterogeneity on the instance level and might result in incompatible database contents. To avoid this kind of heterogeneity, ICD (International Classification of Diseases) and ICPM (International Classification of Procedures in Medicine) need to be used as a controlled terminology, or to incorporate a meta-thesaurus like UMLS. The main goal of Achour and co-authors [Achour et al. 2001] is the design of a knowledge acquisition tool to facilitate the maintenance and creation of a clinical knowledge base by physicians specialists, and its subsequent reuse and sharing by other physician institutions. The tool allows physicians to configure rule-based templates that are mapped to the UMLS-based domain-specific lexicon which they previously constructed based on UMLS Methatesaurs and Semantic Network. Written in Arden Syntax, Medical logic modules are generated to facilitate reuse and sharing of the knowledge base. A semantic Web [Miller et al. 2006c] framework allows Web documents to express meaning about its content, creating an Internet environment where software agents may exchange and find themselves, and mainly, to know about information which only a human being could conclude. RDF (Resoucer Description Framework) [Miller et al. 2006b] and OWL (Ontology Web Language) [Miller and Hendler 2006] are W3C recommended specifications and markup languages to provide model and syntax to Web application developers to better describe documents metadata. A W3C Interest Group named Semantic Web Health Care and Life Sciences [Miller et al. 2006a] was created to enhance Web Semantic technologies application on health care and life science industries, clinical research and medical community. The scope of interest group includes the core vocabularies usage, ontology, and guidelines, and best practices to support cross-community data integration. Kim and co-authors [Kim et al. 2005] propose a prototype tool, called PathOnt. It helps a pathologist during a gross examination (macroscopic report) and inputs narrative records in a structured form. A layered approach is showed to build a GALEN ontologybased application for the pathological gross description using Semantic Web technologies, such as RDF and OWL. This kind of approach enables knowledge modelers and users with different clinical roles to collaborate with each other and facilitates the interactions among different applications using Semantic Web markup languages. Next session we introduce and discuss how medical community can benefit from a computer environment that supports second opinion diagnosis activities.

3. Benefits of a Computer Environment that Support a Second Opinion Diagnosis Activities The scenario of exchanging and sharing Web clinical knowledge among medical community to support a second opinion diagnosis make possible some new medical activities, which are demonstrated, as follows: 1. A physician can build a clinical knowledge database based on his/her real local clinical case database; 2. A physician can publish and share his/her clinical knowledge database over the Internet;

364

3. A physician can discover and retrieve another physician clinical knowledge database over the Internet; 4. A physician can specify a set of symptoms and diagnosis (SD) related to a pathology which, in turn, can be specified based on the his/her experience or on the SD’s frequency. Particularly in this case, a physician’s diagnostic ability may be replaced by a experienced physician discussion board. The set of SD can be used and shared by physicians of the same specialist. An EHS graphical interface may also be automatically configured with structured input fields referring to the same SD suggested; 5. Participating physicians Web community can be responsible to manage and to moderate some interesting situations, as follows: (a) when a physician proposes a new symptom or a new diagnosis to a particular pathology community; (b) when a physician inserts a new clinical case that he/she considers interesting. In both cases, the medical community is responsible to decide whether these data should be relevant to the database or not. In a Web scenario described above, enhanced by a collaborative approach, some interesting situations can be possible, such as: • A less experienced physician may have a second opinion from a shared clinical knowledge database before deciding for a specific diagnostic; • A physician can have a second opinion from three or more different clinical knowledge databases, for example, first from a physician discussion board, them from his/her own knowledge database; and finally from which one another physician knowledge database; • It is also possible for a physician to insert a new case in a shared case database. The decision for the inclusion of the new case maybe moderated by the community via a moderator software agent. This situation is particularly important because it can be used to help the discovery of new diagnostic rules and inferences. This scenario proposed has a potential to enhance discoveries of new pathologies, and can also be used to facilitate accurate statistical findings on health-care. The activities and scenarios presented earlier have some needs: 1. it has to be added as new options into physicians’ actual softwares functionality; 2. it has to be computer platform independent; and 3. the activity of specify, exchange and share a set of SD related to a particular pathology need to be terminology system independent and ontological compatible. It is relevant to mention that to create a software that promotes the exchange of clinical knowledge among medical community via Web to support a second opinion diagnosis, and which supplies the needs presented, it is necessary to deal with technical and semantic problems. Specific solutions to solve these problems are addressed in next session.

4. Technical Interoperability Problems Whether physicians wonder to share medical experiences, they may need Web computer environment to exchange clinical cases and knowledge. To accomplish it, physician’s

365

software needs to call remote procedures between them. Therefore, difficulties should arise for Web users under distinct computer platforms, or heterogeneous computer architecture or yet different program development technology. Figure 1 illustrates a common scenario of technical interoperability problem.

Figure 1. Technical interoperability problem scenario

Additionally to this kind of a problem, where would physicians find a specific remote procedure to create a clinical knowledge database in a particular pathology or a particular remote procedure to get a second opinion diagnosis? And how would a physician notify his/her community that he/she has published his/hers medical knowledge base? Physician’s software needs to publish, and to discover remote procedure in a standard, universal and integrated way. 4.1. How to solve A physician can create, share, and discover a clinical knowledge base, or yet ask for a second opinion diagnosis. To support these clinical activities, a set of four Web services are proposed and illustrate in Figure 2. In this figure we see: 1. Clinical Knowledge Creator Web service (CKCWs): a physician’s software can use the CKCWs to create a clinical knowledge based on his/her clinical cases (symptoms and diagnosis) database, and receive a knowledge database; 2. Second Opinion Diagnosis Web service (SODWs): a physician’s software can use the SODWs to obtain a second opinion diagnosis based on their knowledge database or from another physician knowledge database, and receive a possible diagnosis; 3. Clinical Knowledge Publish Web service (CKPWs): a physician’s software may use the CKPWs to publish and to share their clinical knowledge database to medical community, and receive an UDDI Business Registry subscribe boolean notification; 4. Clinical Knowledge Discover Web service (CKDWs): a physician’s software can use the CKDWs to discover for clinical knowledge database, and receives an endpoints vector. Using UDDI protocol, a physician’s software may publish and discover a clinical knowledge base or a second opinion diagnosis service of his/hers interest. Figure 3 illustrate two situations. The first one illustrates a physician’s or discussion board’s software publishing their CKCWs (1a and 1b). Following that, a physician’s software can fetch for a CKCWs (1c) in a UDDI Business Registry, and receive a pointer response to a WSDL

366

Figure 2. Second Opinion Diagnosis Web Services Support

document. Finally, situation 1d indicates a physician’s software using the Web service discovered. The second one shows a physician’s or discussion board’s software publishing its SODWs (2a and 2b). In 2c, a physician’s software can also look for SODWs in a UDDI Business Registry, and receive a pointer response to a WSDL document. Finally, situation 2d demonstrates a physician’s software using the Web service discovered. Another situation not reported in this Figure is to publish and to discover clinical knowledge database using CKPWs and CKPWs, respectively. However, during the sharing clinical cases and knowledge activities to support a second opinion diagnosis, SD data related to a particular pathology needs to be terminological and ontological compatible for semantic interoperability reasons. Next session aims to discuss and illustrate possible semantic interoperability problems and solutions that occur to support a second opinion diagnosis in a shared environment.

5. Semantically Interoperability Problems Physician’s software usually uses different terminology systems that generate some traditional interoperability problems, for example, how do they know that different strings or terms relates to the same medical concept? Figure 4 illustrates a clinical data exchange example. In this figure, physicians are using different terminology system: MeSH, ICD-10, COSTAR and SNOMED Clinical Trial. All these terminology systems represent the Cholecystitis UMLS concept with different terms or atoms: Gallbladder Inflammation(MeSH), Cholecystitis(ICD-10), INFLAMMATION GALL BLADDER(COSTAR) and Cholecystitis NOS (disorder)(SNOMED Clinical Trial).Each of them correspond to different atom unique identifier (AUI) numbers in the UMLS Metathesaurus. This scenario exploits a semantic terminological problem. Therefore, biomedical software needs to exchange and to share clinical data carrying concepts, a concept unique identifier, a semantic type, and definition associated values. These values need to be associated to an unified medical language system. Semantic problems can be worst if clinical applications uses different ontology which are hard coded into an application database schema. Figure 4 illustrates systems

367

Figure 3. Second opinion diagnosis UDDI support

with different ontologies (HL7, Galen, xDT, and UMLS Semantic Network). Medical vendors are no consensus about a clinical ontology common standard. Ontology such as HL7 are common in hospital setting, but outside it is unusual and other standards might be in use. These medical ontologies cited above have large quantity of classes, object properties, datatypes properties, and restrictions, so that it’s difficult to understand them and to make use by clinical applications. Nevertheless, they were not designed to define a common vocabulary nor a set of data and their structure for physicians and others programs which need to share second opinion diagnosis information. Thus, there is no ontology available neither a proposed one at this context. This kind of scenario implies a semantic ontological problem.

Figure 4. Sharing Clinical Case

5.1. How to solve Figure 5 illustrates SODOnt (Second Opinion Diagnosis Ontology), a clinical ontology to support a second opinion diagnosis in a shared, service oriented, and distributed computer

368

environment. SODOnt is composed of three classes resources: The UMLSType resource : It represents the UMLS essential values from a symptom description, a symptom content value, or a disease opinion such as: concept, concept unique identifier, semantic type, and a definition; The Symptom resource : A symptom needs to be constructed and exchanged with a UMLSType description, and also, with a UMLSType content value; The ClinicalEvaluation resource : It represents all clinical information been transferred: pathology UMLS description, patient symptoms, and an optional UMLSType disease or syndrome opinion. The last ClinicalEvaluation property is optional because obviously physician’s software will not exchange disease information when a second opinion is requested.

Figure 5. SODOnt - Second Opinion Diagnosis Ontology

To share clinical data according to the SODont ontology, a physician’s software needs to create structured documents conformed to protocol or rules set established among medical community. This protocol is formalized with RDF Schema (RDFS), a RDF’s vocabulary description language for describing groups of resources and the relationships among these resources, as well as their domain and range. Next document illustrates a partial RDF Schema 1 used in this proposal. Line 2 defines SODont namespace, an alias that prefix defined resources in all RDF instance documents. From line 5 to 8 is defined ClinicalEvaluation class resource. From line 10 to 16 concept property resource is defined, specifying its range and domain. Finally, from line 17 to 24 a definition of pathologyDescription property resource is found, specifying its range and domain as well. 1 2 3 4 5 6 7 8 9 10 11 12 13

1

A complete SODOnt RDF Schema document can be found at http://143.107.220.180/SODOnt

369

14 15 16 17 18 19 20 21 22

Suppose a physician’s software is exchanging clinical information about his/her patient. Clinical evaluation is concerned to acute abdominal pain pathology. Vomitus symptoms are one of the important aspects to be considered, and bilious finding is their content value. In this example, cholecystitis is a symptom or syndrome second opinion. To exchange these information using Internet, a RDF instance is a suitable specification to use. Next document illustrates a partial well-formed, and valid RDF document conform to SODOnt ontology 2 . It is important to notice that Acute Abdominal Pain, Vomitus, Bilious Finding, and Cholecystitis concepts have UMLSType associated, meaning that physician’s software can understand the transferred data terminology system independently. Line 3 from RDF document indicates SODOnt namespace URI. From line 4 to 9 clinicalEvaluation element has been defined, and it is composed of a pathologyDescription, a symptom, and a diseaseOrSyndromeOpinion instance. From line 10 to 15 an acute abdominal pain pathology instance is created. From line 16 to 19 symptoms are created, and they are composed by symptom instances. From line 20 to 23 vomitus symptom instance is generated. Vomitus symptom description is been created from line 24 to 29. From line 30 to 35 a bilious finding content value instance is been generated. Finally, from line 36 to 44 a cholecystitis diagnosis opinion is created. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

A c u t e Abdominal P a i n C0740577 S i g n o r Symptom None f o u n d Vomitus C0042965 Body S u b s t a n c e None f o u n d Vomit : b i l i o u s f i n d i n g C0427815 L a b o r a t o r y o r T e s t R e s u l t None Found c h o l e c y s t i t i s C0008325 D i s e a s e o r Syndrome I n f l a m m a t i o n o f t h e GALLBLADDER; g e n e r a l l y c a u s e d by i m p a i r m e n t o f BILE flow , GALLSTONES i n t h e BILIARY TRACT, i n f e c t i o n s , o r o t h e r d i s e a s e s . (MeSH)

2

A complete RDF document http://143.107.220.180/SODOnt

conformed

to

SODOnt

RDFS

can

be

found

at

370

Figure 6 illustrates and summarizes SODOnt ontology, CKCWs, SODWs, CKPWs, and CKDWs Web services, UMLS, and Semantic Web. They can be related to solve technical and semantic interoperability problems. As a result, a shared, service oriented, and distributed computer environment is created to support a second opinion diagnosis.

Figure 6. Sharing Knowledge Solved

A use case was implemented to show how computer applications can make use of SODOnt ontology, UMLS, and Web services proposed at this paper to solve technical and semantic problems. Next session, this use case is described.

6. Use Case Implementation The use case implemented can exchange and share acute abdominal pain knowledge and can also support a second opinion diagnosis about this pathology. The following Web services have been implemented and published into two public UDDI Business Registry Node: CKCWs, SODWs, CKPWs, and CKDWs. Two kinds of clients were developed: specialist discussion board and physician softwares. The Java objects oriented language was elected to implement the proposed Web services and physician’s and discussion board’s client softwares. SAX and DOM APIs were chosen to manipulate XML documents. The Apache AXIS Java Web Services 3 API was selected to serve Web services software structure. MySQL was also used as the database manager system to store clinical cases. The next three sub-sessions present how Web services, and client softwares were implemented. 6.1. Second Opinion Diagnosis Web services CKCWs e SODWs were implemented using WEKA API 4 and C4.5 algorithm to execute a decision tree learning machine. Java programs were implemented to publish the Web services at SAP 5 and Microsoft 6 public UDDI Business Registry Node. The situations specialist discussion board and physician’ software clients used Web services are described as follow. 3

http://ws.apache.org/axis/ http://www.cs.waikato.ac.nz/ ml/weka/index.html 5 http://uddi.sap.com 6 http://uddi.microsoft.com 4

371

6.2. Specialist Discussion Board’s software The specialist discussion board created forty signals or symptoms, and fourteen possible diagnoses related to acute abdominal pain. Figure 7 illustrate a frame window developed for SD definition. SD can assume continuous values, as temperature and age, or discrete values, like severity {discomfort, moderate, severe}, and auscultation {normal, metallic sounds, hypoactive, hyperactive, no matter}. The set of SD was initially chosen because of their frequency in acute abdominal pain pathology [Porto 1991]. All SD are defined and created based on UMLS MetaThesaurus concepts and terms, and particularly diagnostics have UMLS Semantic Type Disease or Syndrome associated to it. Figure 8 shows a symptom definition based on a particular terminology system’s term. Severity term from SNOMED Clinical Terms was associated with Severities concept from UMLS Methathesaurus. Thus, concept, cui, semantic type, and definition information from Severities UMLS concept are used to be shared. UMLSKS Java API was used to relate terminology system terms with UMLS Methathesaurus concept.

Figure 7. Symptoms and Diagnosis Definition

Figure 8. Symptoms and Diagnosis Definition based on UMLS

After defining and creating SD values, a specialist discussion group can create clinical cases database. Figure 9 illustrate a frame window designed for acute abdominal pain structured entry data. It was created 211 clinical cases on acute abdominal pain. To create knowledge from its clinical case database, it was necessary to discover and to use CKCWs. A Java program was developed to discover Web services at public UDDI chosen at this project. Finally, to share specialist discussion board knowledge, it was necessary to discover and to use CKPWs. 6.3. Physician’s software Physicians can also produce their own clinical cases database. Figure 10 illustrate a frame window implemented for acute abdominal pain structured entry data. It was developed

372

Figure 9. Creating Clinical Database

Figure 10. Filling Data Entry

26 real cases on acute abdominal pain. To create acute abdominal pain knowledge from a clinical case database, it was necessary to discover and use CKCWs. To import and to utilize another acute abdominal pain knowledge (particularly from specialist discussion group), it was necessary to discover and to use the CKDWs. Having two acute abdominal pain knowledge (from the physician itself and from a discussion board), the physician’s software needs to find and use SODWs. Figure 11 shows a second opinion diagnosis based on specialist discussion group knowledge.

Figure 11. secondOpinionDiagnosis

7. Discussions This paper aimed to discuss and propose a solution to technical and semantic interoperability problems in a shared, service oriented, and distributed computer environment that supports a second opinion diagnosis activities. To solve these problems, CKCWs, SODWs, CKPWs and CKDWs Web services were suggested to be used and solve technical problems. UMLS and Semantic Web were recommended for semantic interoperability. SODOnt ontology and RDF Schema documents were proposed to create a protocol that can be used by medical communities on the Web which wish to exchange and to share clinical documents during second opinion diagnosis activities. Technologies utilized to implement technical interoperability like AXIS Java Web Services and Java UDDI APIs were considered suitable, mainly by computation architecture and programming language independence reasons. These tools are free and available at the Web. Specifications used to develop semantic interoperability like UMLSKS API,

373

RDF and RDF Schema were considered proper. SODont ontology is a novel protocol proposed to support structured and formalized clinical documents that contains symptoms and diagnosis data to support a second opinion diagnosis. This ontology has shown suitable in all implemented use cases. Particular pathology SDs created and shared by a physician or specialist discussion groups are specified at WSDL specification for common knowledge reasons. If a physician considers some SDs that are not considered by an imported knowledge database, ‘nomatter‘ values are assigned to these SDs. The impact of this decision is been studied nowadays. Authors will be in discussion soon with a health institute in order to offer the use of second opinion diagnosis Web services, and SODOnt ontology protocol by resident medical students. This action can accuratly contribute to solve technical and semantic interoperability problems. Undergraduates can also create a new pathology case to be tested. A SODOnt API based on JAXB (Java Architecture for XML Binding )has been created by authors with classes and methods to help physician’s softwares to exchange and share XML clinical documents. Finally, an use case is being developed at TIDIA-Ae project context with LSCUniCOC/UFSCar laboratory. This particular use case will apply the research in an elearning environment.

Acknowledgement This project has been supported by FAPESP (03/08274-0)

References Achour, S., Dojat, M., Rieux, C., Bierling, P., and Lepage, E. (2001). A umls-based knowledge acquisition tool for rule-based clinical decision support system development. Journal of American Medical Informatics Association, 8(4):351–360. Aloisio, G., Blasi, E., Cafaro, M., Fiore, S., Lezzi, D., and Mirto, M. (2003). Web services for a biomedical imaging portal. In Proceedings of the International Technology: Computers and Communications. IEEE Computer Society, volume 1, pages 432–436. Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The semantic web. Scientific American, 5:28–37. Beyer, M., Kuhn, K., Meiler, C., Jablonski, S., and Lenz, R. (2004). Towards a flexible, process-oriented it architecture for an integrated healthcare network. In Proceedings of the 2005 ACM symposium on Applied computing - Computer applications in health care (CAHC), volume 1, pages 264–271. Booth, D., Haas, H., McCabe, F., Newcomer, E., Champion, M., Ferris, C., and Orchard, D. (2006). Web service architecture w3c working group, http://www.w3.org/tr/wsarch/. Chinnici, R., Gudgin, M., Moreau, J., Schlimmer, J., and Weerawarana, S. (2006). Web services description language (wsdl) version 2.0 part 1: Core language, http://www.w3.org/tr/2004/wd-wsdl20-20040803/.

374

Demiris, G. (2003). Integration of telemedicine in graduate medical informatics education. Journal of American Medical Informatics Association, 10(4):310–314. Ho, K., Karlinsky, H., Selinger, S., and May, J. (2004). Videoconferencing for telehealth: Unexpected challenges and unprecedented opportunities. British Columbia Medical Journal, 46(6):133–140. Joubert, M., Aymard, S., Fieschi, D., Volot, F., Staccini, P., Robert, J., and Fieschi, M. (1998). Ariane: Integration of information databases within a hospital internet. International Journal of Medical Informatics, 49(3):297–309. Joubert, M., Dufour, J.-C., Falco, L., Aymard, S., , and Fieschi, M. (2004). Towards interoperability of heterogeneous health databases: application to a tumor samples bank. MEDINFO, 11(2):1251–1255. Kim, H.-G., Ha, B.-H., Lee, J.-I., and K., M.-K. (2005). A multi-layered application for the gross description using semantic web technology. International Journal of Medical Informatics, 74(5):399–407. McCray, A. and Nelson, S. (1995). The representation of meaning in the umls. Methods Inf Med., 34(1-2):193–201. Miller, E. and Hendler, J. http://www.w3.org/2004/owl/.

(2006).

Web

ontology

language

(owl),

Miller, E., Hongsermeier, T., Neumann, E., and Gilman, B. (2006a). W3c semantic web health care and life sciences interest group, http://www.w3.org/2001/sw/hcls/. Miller, E., Swick, R., and Brickley, D. (2006b). Resource description framework (rdf), http://www.w3.org/rdf/. Miller, E., Swick, R., Brickley, D., McBride, B., Hendler, J., Schreiber, G., Wood, D., and Connolly, D. (2006c). Semantic web activity, http://www.w3.org/2001/sw. Mitra, N. (2006). Soap version 1.2 part 0: Primer, http://www.w3.org/tr/2003/rec-soap12part0-20030624/. ¨ Müller, M. L., Uckert, F., Bürkle, T., and Prokosch, H. (2005). Cross-institutional data exchange using the clinical document architecture (cda). International Journal of Medical Informatics, 74(2–4):245–256. Pires, D., Halah, R., Tinos, R., and Ruiz, E. (2005). An architecture to support clinical knowledge sharing among medical community via internet. In Proceedings of the V Workshop de Informática Médica. Congresso Brasileiro de Qualidade de Software., volume 1, pages 114–124. Porto, C. (1991). Semiologia Médica. Editora Guanabara Koogan. Stal, M. (2002). Web services: beyond component-based computing. Communication of ACM, 45(10):71–76. Uddi (2006). Oasis http://www.uddi.org/.

uddi

advancing

web

services

discovery

standard,

Umls (2006). Unified medical language system - national library of medicine, http://www.nlm.nih.gov/research/umls/.

375