An Investigation on Various Learning Ontology Methods using in Medical Systems

R. Aravazhi, M. Chidambaram


Universal health researchers are creating, editing, investigating, incorporating, and storing huge amounts of digital medical statistics daily, through observation, testing, and replication. In the event that we could viably exchange and coordinate information from every single conceivable asset, at that point a more profound comprehension of every one of these informational indexes and better uncovered learning, alongside fitting bits of knowledge and activities, would be allowed. Tragically, as a rule, the information clients are not the information makers, and they in this way confront challenges in tackling information in unanticipated and spontaneous ways. With a specific end goal to get the capacity to incorporate heterogeneous information, and along these lines proficiently alter the customary therapeutic and organic research, new approaches created upon the undeniably inescapable cyberinfrastructure are required to conceptualize conventional medical and biological data, and gain the "profound" knowledge out of unique information from that point. As formal information portrayal models, ontologies can render precious help in such manner. In this paper, we shorten the state-of-the-art research in ontological systems and their creative application in medical and biological areas.

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G.Leroy, H.Chen, “Meeting medical terminology needs-the ontology-enhanced Medical Concept Mapper” IEEE Trans.on Information Technology in Biomedicine, Vol.5, No.4, PP.261 – 270, 2001.

U.Hahn, S.Schulz, M.Romacker, “Part-whole reasoning: a case study in medical ontology engineering”, IEEE Intelligent Systems and their Applications, Vol.14, No.5, PP.59 – 67, 1999.

N.Larburu, R.G.A.Bults, M.J.Van Sinderen, I.Widya, H.J.Hermens, “An Ontology for Telemedicine Systems Resiliency to Technological Context Variations in Pervasive Healthcare”, IEEE Journal of Translational Engineering in Health and Medicine, Vol.3, Article Sequence Number: 2900110, 2015.

J.D.Fernández, M.Lenzerini, M.Masseroli, F.Venco, S.Ceri, “Ontology-Based Search of Genomic Metadata”, IEEE/ACM Trans. on Computational Biology and Bioinformatics, Vol.13, No.2, PP.233 – 2, 2016.

T.Nguyen, C.Mitrea, R.Tagett, S.Draghici, “DANUBE: Data-Driven Meta-ANalysis Using UnBiased Empirical Distributions—Applied to Biological Pathway Analysis”, Proceedings of the IEEE, Vol.105, No.3, PP.496 – 515, 2017.

B.Jafarpour, S.R.Abidi, S.S.Raza Abidi, “Exploiting Semantic Web Technologies to Develop OWL-Based Clinical Practice Guideline Execution Engines”, IEEE Journal of Biomedical and Health Informatics, Vol.20, No.1, PP.388 – 398, 2016.

Sheau-Ling Hsieh, Wen-Yung Chang, Chi-Huang Chen, Yung-Ching Weng, “Semantic Similarity Measures in the Biomedical Domain by Leveraging a Web Search Engine”, IEEE Journal of Biomedical and Health Informatics, Vol.17, No.4, PP.853 – 861, 2013.

I.Berges, J.Bermudez, A.Illarramendi, “Toward Semantic Interoperability of Electronic Health Records”, IEEE Trans. on Information Technology in Biomedicine, Vol.16, No.3, PP.424 – 431, 2012.

C.Bratsas, P.Bamidis, D.D.Kehagias, E.Kaimakamis, N.Maglaveras, “Dynamic Composition of Semantic Pathways for Medical Computational Problem Solving by Means of Semantic Rules”, IEEE Trans.on Information Technology in Biomedicine, Vol.15, No.2, PP.334 – 343, 2011.

H.Al-Mubaid, H.A.Nguyen, “Measuring Semantic Similarity Between Biomedical Concepts Within Multiple Ontologies”, IEEE Trans.on Systems, Man, and Cybernetics, Part C (Applications and Reviews), Vol.39, No.4, PP.389 – 398, 2009.

G.Leroy, H.Chen, “Meeting medical terminology needs-the ontology-enhanced Medical Concept Mapper”, IEEE Trans.on Information Technology in Biomedicine, Vol.5, No.4, PP.261 – 270, 2001.

Ana Bertha Rios Alvarado, Ivan Lopez Arevalo, Edgar Tello Leal, “The acquisition of axioms for ontology learning using named entities”, IEEE Latin America Transactions, Vol.14, No.5, PP.2498 – 2503, 2016.

R.Y.K.Lau, Dawei Song, Y.Li, Terence C.H.Cheung, Jin-Xing Hao, “Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning” IEEE Trans.on Knowledge and Data Engineering, Vol.21, No.6, PP.800 – 813, 2009.

A.Maedche, S.Staab, “Ontology learning for the Semantic Web”, IEEE Intelligent Systems, Vol.16, No.2, PP.72 – 79, 2001.

M.Missikoff, R.Navigli, P.Velardi, “Integrated approach to Web ontology learning and engineering”, Computer, Vol.35, No.11, PP.60 – 63, 2002.

J.N.K.Liu, Yu-Lin He, Edward H.Y.Lim, Xi-Zhao Wang, “A New Method for Knowledge and Information Management Domain Ontology Graph Model”, IEEE Trans.on Systems, Man, and Cybernetics: Systems, Vol.43, No.1, PP.115 – 127, 2013.



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