Generation Of Personalized Ontology Based On Treatment
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp.12096- 12101 Research India Publications. http://www.ripublication.comGeneration of Personalized Ontology based on treatment schemes utilizingsemantic rules for HPVR.Geetha and S.Sivasubramanian1Research Scholar, Bharath University, 173, New Agaram Rd, Selaiyur, Chennai, Tamil Nadu 600073, India.2Principal, Dhanlakshmi College of Engineering, Dr. V. P. R Nagar, Off. Tambaram Sriperumbudur Road,Manimangalam Post, Chennai, Tamil Nadu - 601 301, India.1Orcid Id: 0000-0003-4631-2475AbstractA dramatic increase of demand for providing treatmentquality has occurred during last decades. The main challengeis to increase the treatment quality. The personalization oftreatment is a must, since each patient constitutes a uniquecase. Health care provision encloses complex remultidisciplinary. So create the conceptualization of DiseaseTreatment Ontology for HPV. The Disease-TreatmentOntology HPVDt ontology comprises: The Clinical Pathwaypart, the quality assurance part, Details about virus, cost oftreatments and diet maintenance. To explore humanpapillomavirus (HPV) occurrence in the great prevalenceregions of cervical cancer and to educate the relationshipamongst HPV contagion and cervical cancer HPVDt ontologyis utilized. Viral load computation is a life-threateningrequirement for HPV administration universally. Theinvestigative tools presently existing are excessively restrictedby their dimension and expenditure to spread numerousisolated and source-restricted residents. Hence HPVDtontology is used for further investigation.Keywords: Adaptive clinical pathway, clinical pathwayontology, personalized treatment.Current web’s extension is semantic web. The Semantic Webis a collaborative movement led by the international standardsbody, the World Wide Web Consortium (W3C). The standardpromotes common data formats that remain in the WorldWide Web. By encouraging the inclusion of semantic contentin web pages, the Semantic Web aims at converting thecurrent web, dominated by unstructured and semi-structureddocuments into a "web of data". The Semantic Web stackbuilds on the W3C's Resource Description Framework (RDF).According to the W3C, "The Semantic Web provides acommon framework that allows data to be shared and reusedacross application, enterprise, and community boundaries”.The term was coined by Tim Berners-Lee for a web of datathat can be processed by machines.A HPV cancer is one which is undoubtedly affected by HPV.HPV origins all cervical cancers and numerous cancers of theoropharynx, rectum, anus, penis, vulva and vagina. Ananalysis based population-used data as of cancer tissue toevaluate the proportion of cancers which are possibly initiatedby HPV. In order to discover the numerous HPV-attributablecancers, the quantifiable HPV-related cancer is multiplied bythe proportion of the cancers which are possibly instigated byHPV. 5,229 people are identified by anal cancer everyrespective year, and almost 91% among anal cancers remainto be affected by HPV. 4,800 is 91% of 5,229.INTRODUCTIONOntology typically consists of a finite list of terms and therelationships between these terms. The terms denote importantconcepts (classes of objects) of the domain, while therelationships include hierarchies of classes. Ontology mayalso include other information, such as properties, valuerestrictions, disjointedness statements, and specifications oflogical relationships between objects. Ontology languages aresemantic markup languages for defining ontology’s. WebOntology Language (OWL) was used, which was proposed asW3C Recommendation, for ontology specification. OWLfacilitates greater machine interoperability of web contentthan XML, RDF, and RDF Schema by providing additionalvocabularies along with a formal semantics.The increment of treatment quality with decrement ofhealthcare provision costs is to be achieved for HPV.Modeling and utilization of standardized Clinical Protocolsused in various domain of medical practice. Standardizedclinical protocols comprise details:1.Medical plans2.Corresponding actions for diagnosis3.Treatment Scheme4.Follow up.12096
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp.12096- 12101 Research India Publications. http://www.ripublication.comFlow of clinical pathwayIn [4] Syed Sibte et al Modeling the Form and Function ofClinical Practice Guidelines: An Ontological Model toComputerize Clinical Practice Guidelines System to SupportChronic Disease Healthcare is experimented.In [5] Jiangbo Dang, An ontological knowledge frameworkfor adaptive medical workflow, Ontologies are a formaldeclarative knowledge representation model. It provides afoundation upon which machine understandable knowledgecan be obtained and as a result it makes machine intelligencepossible. Healthcare systems can adopt these technologies tomake them ubiquitous, adaptive, and intelligent and then servepatients better.In [6] W.E.McCarthy the REA accounting model, thegeneralized framework for accounting system in a shared dataenvironment is analyzed. The REA model is a technique forcapturing information about economic pheno mena. Itdescribes a business as a set of economic resources, economicevents and economic agents as well as relationships amongthem.Figure 1: Flow of clinical pathway“Clinical pathways” Fig.1 is the effective and efficient tool toachieve the above mentioned objectives.Clinical pathways allow the design and implementation ofmedical guidelines in a specific healthcare environment anddecrease the occurrence of any undesired variability ofmedical practice. Disease-Treatment Ontology facilitatesdynamic CP utilization for the development of Semantic WebRules.RELATED WORKIn [1]Dimitrios AI et al SEMPATH Ontology: ModelingMultidisciplinary Treatment Schemes Utilizing Semantics,allows the conceptual modeling of the multidisciplinaryentities engaged in the execution of CP (medical,organizational, financial worlds modeling) in a consistentway, leveraging the further utilization of the semanticinfrastructure.In [2] Marut BURANARACH et al Design andImplementation of an Ontology-based Clinical Reminder,describes an ontology-based information and knowledgemanagement framework that is important for chronic diseasecare management. The framework is designed to support twochronic care components: clinical information system anddecision support.In [3] Christopher S.G. Khoo et al Developing an Ontologyfor Encoding Disease Treatment Information in MedicalAbstracts, Disease-Treatment ontology which representsspecific treatments that are considered for a particular disease,are described in medical articles.In [16] Rachid Benlamri et al Building a Diseases SymptomsOntology for Medical Diagnosis, An Integrative approachMedical ontologies are valuable and effective methods ofrepresenting medical knowledge is investigated. In thisdirection, they are much stronger than biomedicalvocabularies. In the process of medical diagnosis, eachdisease has several symptoms associated with it. There arecurrently no ontologies that relate diseases and symptoms andonly attempts at their infancy along with some simpleproposed models exists.In 1842 Rigoni-Stern first observed cervical cancer was foundin married women and almost lacking in catholic nuns.Scientists concentrated on etiologic sources, which aretransmitted by sexual contact. Human Papilloma-Virus (HPV)is the main source for sexually transmitted disease resulting incervical cancer in women.HPV is responsible for squamousepithelial warts and lesions. Richard E. Shope was the first toexamine cottontail rabbit and detached papillomavirus fromwarts (Shope & Hurst, 1933). As the result of thisexamination different types of papillomaviruses were isolatedboth from plants and animals. Infection in humans is causedby a group of Papillomavirus called Human papillomaviruses.Human papillomavirus belongs to small DNA virus familyknown as papillomaviridae.Purola and Savia examined and stated the occurrence of HPVin dysplastic squamous epithelial cells in 1977. HPV ispresent in the nuclei of dysplastic squamous epithelial cellswhich has koilocytotic features. This examination wasconfirmed by ZurHausen and Gissman in 1980 which statesthat this virus is inevitable for cervical cancer.Syrjanen et al. (2004) investigated the tariffs of attainmentand the period of occurrence highrisk (HR) humanpapillomavirus (HPV) contaminations and Pap smear12097
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp.12096- 12101 Research India Publications. http://www.ripublication.comirregularities and their extrapolative issues were in 423womenfolk partaking in a multicenter screening learning andresolved that the attainment of HR HPV infection issuggestively age reliant. Third, Diet part tells about diet maintenance of the patients.Souho et al. (2015) studied the lessons from 1994 to 2014 andestablished that HPV septicity is expressively related tonumerous contrary possessions on the generative fitness ofboth well-being and likewise modifies their productivenessfrequency.Fig. 2 illustrates the system architecture for HPVDt ontology.To develop Disease-Treatment ontology based on theontology-based information and knowledge managementcomprise a set of evidence-based recommendations to bothstandardize and optimize the care process whilst ensuringpatient safety and quality of care.Wilting and Steenbergen (2016) encapsulates in what wayHPV oncogenes own added possessions which affect usingthe DNA methylation machinery and mitotic checkpoints andcontinue to unusual assessment neoplasia or cancer and ourexisting information about the molecular alterations in themass genome which happens throughout HPV-inducedcarcinogenesis assist us to rise considerate almost cervicalcancer, to obtain biomarkers for initial analysis and torecognize therapeutic objectives for HPV persuadedprecancerous tissue.Proposed WorkEach patient is considered as unique and the real challenge tobe provoked is to proliferate treatment quality in thepersonalization that lies in the treatment. Health careprovision remains multidisciplinary which comprisescomplicated environment. A conceptualization for the domainof clinical pathways (CP) has been introduced. The treatmentfor disease in ontology constitutes three parts.1.Part defining clinical path2.Information part regarding virus.3.Diet part and risk assessment.System ArchitectureAn ontology-based information and knowledge managementprocess comprises a set of functional and temporal constraints,desired outcomes, set of actions and decision criterion. Atypical disease, as a dependent continuant, enacts extending,branching, and fading processes before it disappears.(i) The set of candidate ontology-based information andknowledge management were studied to extract and explicatethe clinical knowledge.(ii) ontology-based information and knowledge managementelements were identified and analyzed, which led to either thespecification of new or the refinement of existing ontologyclasses, attributes and constraints to model the ontology-basedinformation and knowledge management elements.A conceptualization for the multidisciplinary domain isobtained by this execution in healthcare provision. Thisexecution is later used for the implementation of SWRL rules(Semantic Web Rules) repository. Modeling, implementingand execution of CP require conceptualization enclosingmultidisciplinary domain of knowledge. First, Guidelines for clinical practice are becoming evermore popular in every sector of healthCare. Guidelines havethe goal of indicating the decisions and tasks most appropriatefor optimizing health outcomes and for controlling costs. Theycan be expressed either in the form of textualrecommendations or as protocols or flow diagram.Standardized clinical protocols comprise details aboutMedical plans, Corresponding actions for diagnosis,Treatment Scheme, Follow up. Second, Virus Information is providing the totalinformation's about virus such as Virus name, Virus Stage,Type, Symptoms. Risk Assessment is providing theinformation about side effect and Disease Effect.Figure 2: Architectural diagram of HPVDt ontology(iii) Changes to the ontological model were reevaluated toensure semantic consistency.12098
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp.12096- 12101 Research India Publications. http://www.ripublication.com(iv) Virus information and diet - Retrieval modules are used toextract the relevant information from the ontology whichconsists of set of rules.CLASSIFICATIONThis fig.3 shows the detailed information about the viruses,treatment schemes and their symptoms.IMPLEMENTATIONOperative information illustration necessitates the usage ofconsistent terminologies to guarantee together pooledunderstanding amongst individuals and interoperability amidinfo schemes. Unexpectedly numerous prevailing biomedicalterminology principles rest on unfinished, varying ordisordered explanations of elementary expressions concerningto infections, diagnoses, and medical phenotypes.A skeleton of what is trusted to be is reasonably andorganically comprehensible structure for the illustration ofentities and the associations amongst them. An observation ofinfection is preserved which are included in every singlecircumstance with physical base inside the creature thattolerates a temperament on the way to the implementation ofpathological progressions.Figure 3.1: Graphical View of HPVDt OntologyThis system comprises of:1.System trieval4.User Interface ModuleandKnowledgeFig.3.1 shows the graphical view of Ontology is used todetermine different relation among the classes, objects andproperties.Ontology based Information and Knowledge ManagementSystem ManagementThis module parses information from the medical datacollection and adds them to the Ontology.This includes data analysis and indexing, these two steps areused to classify the data based on their behaviors and used tocreate the Disease-treatment ontology and update theinformation’s based on the clinical path ways.The main building block of ontology is the concept of a class.The ontology defines numerous classes that permit theexplanation of research data. Objects possess the entirety ofinformation for a particular study. Classes describe theindependent variables of the research. Each variable identifythe attributes to its instance. Subclasses describe the dependent variables, the values is from investigational trials.These classes describe metrics, the values is obtained fromeach participant during the research.Objects, instances of the classes explain a fixed value of afeature. This determines the membership to a particular cell ofthe research design matrix. Classes describe a particularDependent Variable.Ontology-based information and knowledge managementfocuses on providing information and knowledge support on1.Virus information2.Risk Assessment3.Clinical Protocol4. Cost estimation.Virus Information is providing total information such as Virusname, Virus Stage, Type, Symptoms.Figure 3: HPVDt ontology - Disease-Treatment Ontology12099
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp.12096- 12101 Research India Publications. http://www.ripublication.comRisk Assessment is providing the information about sideeffect and Disease Effect.Code snippet for HPVDt ontologyStandardized clinical protocols comprise details aboutMedical plans, Corresponding actions for diagnosis,Treatment Scheme and Follow up.RETRIEVALRetrieval modules are used to extract the relevant informationfrom the ontology. The design and development of theDisease-treatment ontology leverages the design andrepresentation of the semantic rules utilizing the SWRL(Semantic Web Rule Language) format. SWRL facilitates theintegration of the modeled rules with the Disease-treatmentOntology. The interaction between rules and ontology leads tonew knowledge through the generation of new facts to beinserted as new concepts.The Semantic Web Rule Language (SWRL) is arecommended language for the Semantic related web which isto define rules and logic, with OWL DL or OWL Lite havingRule Markup Language as subset (subset of Datalog).XML Coding:SWRL decides the practical implementations of OWL DLwhich is regained by limiting the method of permissible rulesby imposing an appropriate well-being situation.Rules are between an antecedent (body) and consequent(head) which implies that if consequent conditions hold it isthe condition that is held in antecedent.XSLT transformation is extended for OWL XML Presentationsyntax which implies the implication.Translation from the XML Concrete Syntax to RDF/XMLcould be easily accomplished by extending the XSLTtransformation for the OWL XML Presentation syntax.RESULTThe HPVDt ontology predicts the prevalence and existence ofHPV. This existence is depicted using the Fig. 4 whichpredicts how far the existence of HPV has been protruded inthe existing population.User Interface ModuleThis module provides the system’s functionality to its users. Itincludes the following1.use the application2.where the user uses the system's functionality3.where the user enters a query4.retrieves relevant documents and reformulates thequery5.if the results are inefficient answer the queryFigure. 4: Graph for the prevalence of HPV based on yearspresent results to user, reformulate the user's query,where the user's query is expanded with new terms.CONCLUSIONThe modeling, implementation, and execution of HPVDtontology require extensive conceptualization since it encloses12100
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp.12096- 12101 Research India Publications. http://www.ripublication.coma highly multidisciplinary domain of knowledge. A diseaseencompasses with physical disorder and treatment Schemes.Cover information’s about virus and diet for patients and rulesfor are used to extract the information from ontology. Thefuture work of this project is to expand the HPVDt ontologyand generate more rules for user extraction.REFERENCES[1]Sempath Ontology: Modeling MultidisciplinaryTreatment Schemes Utilizing Semantics. DimitriosAi.Alexandrou, Konstantinos V.Pardalis.[2]Design And Implementation Of An Ontology-BasedClinical Reminder System To Support ChronicDisease Healthcare (Marut Buranarach, NopphadolChalortham, Ye Myat Thein, Nonmembers,AndThepchai Supnithi†,Regular Member)Ieice Trans.Fundamentals/Commun./Electron./Inf. & Syst., Vol.E85-A/B/C/D, No. Xx January 2011.[3]Developing An Ontology For Encoding DiseaseTreatment Information In Medical Abstracts(Christopher S.G. Khoo, Jin-Cheon Na, Vivian WeiWang*, And Syin Chan) Desidoc J. Lib. Inf. Technol.,2011, 31(2).[4]Modeling the Form And Function Of ClinicalPractice Guidelines: An Ontological Model ToComputerize Clinical Practice Guidelines (Syed SibteRaza Abidi And Shapoor Shayegani).[5]An Ontological Knowledge Framework for AdaptiveMedical Workflow Jiangbo Dang, Amir Hedayati,Ken Hampel, Candemir nload/Index.Html[7]O. Bodenreider, B. Smith, A. Kumar, And A Burgun,‘Investigating Subsumption In Snomed Ct: AnExploration Into Large Description Logic-BasedBiomedical Terminologies’, Journal Of ArtificialIntelligence In Medicine, 39, 183–195, (2007).[8]Richard H. Scheuermann, PhD, Werner Ceusters,Md, Toward An Ontological TreatmentOf DiseaseAnd 3.org/ Submission/SWRL.[10]S.W. Tu, J. Campbell, and. A.Musen, “The SAGEguideline modeling: Motivation and methodology,”Stud. Health Technol. Inform., vol. 101,pp. 167–171,2004.[11]G. L. Geerts and W. E. McCarthy, “An ontologicalanalysis of the primitives of the extended-REAenterprise information architecture,” Int. J.Accounting Inf. Syst., vol. 3, pp. 1–16, 2000.[12]European Foundation for Quality ManagementExcellence Model. (Jun.2010)[Online]. Available:http://www.efqm.org/en/13) Agency for line].Available:http://www.qualityindicators. ahrq.gov[13]Smith B, Ashburner M, Rosse C, Bard J, BugW,Ceusters W, Goldberg LJ, Eilbeck K, IrelandA,Mungall CJ, Leontis N, Rocca-Serra P, RuttenbergA,Sansone SA, Scheuermann RH, Shah N, WhetzelPL,Lewis S. The OBO Foundry: Coordinatedevolutionof ontologies to support biomedical dataintegration,Nature Biotechnology 2007; 25 (11):1251-1255.[14]Schulz S, Johansson I. Continua in biological systems.The Monist, 2007; 90(4): 499-22.[15]Williams, N. The factory model of disease. TheMonist, 2007; 90(4): 555-584.[16]Osama Mohammed, Rachid Benlamri, Building aDiseases Symptoms Ontology for Medical Diagnosis:An Integrative Approach.[17]A. Woo, “Demo Abstract: A New Embedded WebServices Approach to Wireless Sensor Networks”, inProc. of the 4th international conference on Embeddednetworked sensor systems, Boulder, Colorado, USA,2006.[18]JENA: A Semantic Web Framework for Java[Online]. Available at: http://jena.sourceforge.net[19]R. Bernazzani, F. Paganelli, D. Chini, A. Mamelli,“ERMHAN una piattaforma multicanale per ilsupporto collaborativo a operatori sanitari mobile”,presented at the 7th National Conference of ItalianAssociation of Telemedicine and Medical Informatics,Turin, 2006.[20]J. Bohn, F. Gartner, H. Vogt, “Dependability Issues ofPervasive Computing in a Healthcare Environment”,in Proc. of the First International Conference onSecurity in Pervasive Computing, Boppard, Germany,March 12-14, 2003.Available:12101
examine cottontail rabbit and detached papillomavirus from warts (Shope & Hurst, 1933). As the result of this examination different types of papillomaviruses were isolated both from plants and animals. Infection in humans is caused by a group of Papillomavirus called Human papillomaviruses.
community-driven ontology matching and an overview of the M-Gov framework. 2.1 Collaborative ontology engineering . Ontology engineering refers to the study of the activities related to the ontology de-velopment, the ontology life cycle, and tools and technologies for building the ontol-ogies [6]. In the situation of a collaborative ontology .
method in map-reduce framework based on the struc-ture of ontologies and alignment of entities between ontologies. Definition 1 (Ontology Graph): An ontology graph is a directed, cyclic graph G V;E , where V include all the entities of an ontology and E is a set of all properties between entities. Definition 2 (Ontology Vocabulary): The .
To enable reuse of domain knowledge . Ontologies Databases Declare structure Knowledge bases Software agents Problem-solving methods Domain-independent applications Provide domain description. Outline What is an ontology? Why develop an ontology? Step-By-Step: Developing an ontology Underwater ? What to look out for. What Is "Ontology .
ontology database, we can answer queries based on the ontology while automat-ically accounting for subsumption hierarchies and other logical structures within each set of data. In other words, the database system is ontology-driven, com-pletely hiding underlying data storageand retrieval details from domain experts,
Ontology provides a sharable structure and semantics in knowledge management, e-commerce, decision-support and agent communication [6]. In this paper, we described the conceptual framework for an ontology-driven semantic web examination system. Succinctly, the paper described an ontology required for developing
An Automatic Ontology Generation Framework with An Organizational Perspective . lack of fully-automated domain-independent ontology generation systems that address common data quality issues. The framework utilizes refined KGs to
A Framework for Ontology-Driven Similarity Measuring Using Vector Learning Tricks Mengxiang Chen, Beixiong Liu, Desheng Zeng and Wei Gao, Abstract—Ontology learning problem has raised much atten-tion in semantic structure expression and information retrieval. As a powerful tool, ontology is evenly employed in various
This research investigates how these technologies can be integrated into an Ontology Driven Multi-Agent System (ODMAS) for the Sensor Web. The research proposes an ODMAS framework and an implemented middleware platform, i.e. the Sensor Web Agent Platform (SWAP). SWAP deals with ontology construction, ontology use, and agent
