Conference Paper

An Ontology-Driven Search Module for Accessing Chronic Pathology Literature.

Conference: On the Move to Meaningful Internet Systems: OTM 2011 Workshops - Confederated International Workshops and Posters: EI2N+NSF ICE, ICSP+INBAST, ISDE, ORM, OTMA, SWWS+MONET+SeDeS, and VADER 2011, Hersonissos, Crete, Greece, October 17-21, 2011. Proceedings
Source: DBLP


This paper presents an advanced search module for bibliography retrieval developed within the CHRONIOUS European IP project. The developed search module is specifically targeted to clinicians and healthcare practitioners searching for documents related to Chronic Obstructive Pulmonary Disease (COPD) and Chronic Kidney Disease (CKD). To this aim, the presented tool exploits two pathology-specific ontologies that allow focused document indexing and retrieval. Besides the search module, an enrichment tool is provided to maintain and to keep up-to date such as ontologies. In addition link with the terms of the MeSH (Medical Subject Heading) thesaurus has been provided to guarantee the coverage with the general certified medical terms and multilingual capabilities.

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Available from: Riccardo Albertoni,
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    • "Pubmed [16] is probably the first search engine used for such purpose. Lots of information are also stored in documentation that is present only in the medical structure, so we equipped Chronious with a an ontology search engine [17] that starting from raw document uses an personalized ontology to grab meanings for the two diseases covered by Chronious [18] [19] [19]. This with the goal of having a fast way for clinician, to find information related to COPD/CKD. "
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    ABSTRACT: CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touch screen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic diseases and to help clinician in taking decision for cure purpose. This paper illustrates how some machine learning algorithms and a rule based decision support system are used in the CHRONIOUS project, to monitor chronic patient. We will analyse how a set of machine learning algorithms can be used in smart devices to alert the clinician in case of a patient health condition worsening trend
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    ABSTRACT: Ontologies have proven to be useful in the area of Information Retrieval and the biomedical informatics community has acknowledged, in recent years, their utility. However, building and updating manually ontologies is a long and tedious task. This paper proposes a system that allows any search engine to develop its semantic layer by applying ontology learning techniques on Web snippets and applies it to a well-known medical digital library, PubMed. The new system (SemPubMed) automatically builds new ontology fragments related to the user’s query and then it reformulates queries using the new concepts in order to improve information retrieval. Our system has endured a twofold evaluations. On the one hand, we have evaluated the quality of the modular ontologies built by the system. On the other hand, we have studied how the semantic reformulation of the queries has led to an improvement of the quality of the results given by PubMed, both in terms of precision and recall. Obtained results show that adding semantic layer to PubMed enables an improvement of query reformulation and predicted ranking score.
    Multimedia Tools and Applications 10/2014; 72(3). DOI:10.1007/s11042-013-1527-4 · 1.35 Impact Factor