Generation and Management of a Medical Ontology in a Semantic Web Retrieval System

Bontas, Elena Paslaru; Tietz, Sebastian; Tolksdorf, Robert; Schräder, Thomas

doi:10.1007/978-3-540-30468-5_41

Cited by 12 publications

(6 citation statements)

References 12 publications

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“…This study developed a web-based prototype for an Integrated Mobile Information System (IMIS) for diabetic patient care [ 20 ]. The authors used ontology mapping so that related organizations could access each other's information.…”

Section: Discussionmentioning

confidence: 99%

“…Web Ontology Language (OWL), Resource Description Framework (RDF), and SPARQL were also commonly used for the creation of metadata in dementia diagnosis [ 77 ]. On the other hand, the Semantic Web-based retrieval system for the pathology project, known as “A Semantic Web for Pathology,” involves building and managing ontology for lungs which was made up of common semantic tools RDF and OWL which were used along with RDQL query language [ 20 ].…”

Section: Analysis Of the Selected Articles: Thematic Areasmentioning

confidence: 99%

“…Kumari et al [ 18 ] and Haque et al [ 19 ] proposed an Android-based personalized healthcare monitoring and appointment application that considers the health parameters such as body temperature, blood pressure, and so on to keep track of the patient's health and provide in-home medical services. Some existing ontologies of medicine are Gene, NCI, GALEN,LinkBase, and UMLS [ 20 ]. They have also been used in offering e-healthcare systems based on GPS tracking and user queries.…”

Section: Introductionmentioning

confidence: 99%

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Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues

Haque

Arifuzzaman

Siddik

et al. 2022

International Journal of Clinical Practice

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Today, healthcare has become one of the largest and most fast-paced industries due to the rapid development of digital healthcare technologies. The fundamental thing to enhance healthcare services is communicating and linking massive volumes of available healthcare data. However, the key challenge in reaching this ambitious goal is letting the information exchange across heterogeneous sources and methods as well as establishing efficient tools and techniques. Semantic Web (SW) technology can help to tackle these problems. They can enhance knowledge exchange, information management, data interoperability, and decision support in healthcare systems. They can also be utilized to create various e-healthcare systems that aid medical practitioners in making decisions and provide patients with crucial medical information and automated hospital services. This systematic literature review (SLR) on SW in healthcare systems aims to assess and critique previous findings while adhering to appropriate research procedures. We looked at 65 papers and came up with five themes: e-service, disease, information management, frontier technology, and regulatory conditions. In each thematic research area, we presented the contributions of previous literature. We emphasized the topic by responding to five specific research questions. We have finished the SLR study by identifying research gaps and establishing future research goals that will help to minimize the difficulty of adopting SW in healthcare systems and provide new approaches for SW-based medical systems’ progress.

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Section: Discussionmentioning

confidence: 99%

Section: Analysis Of the Selected Articles: Thematic Areasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues

Haque

Arifuzzaman

Siddik

et al. 2022

International Journal of Clinical Practice

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“…Ones of the best known medical taxonomies are: GALEN [6] (basic clinical concepts — fracture, bone, and so on — controlling combinations of related concepts — bone fractures — and complex concepts — clavicle fracture), UMLS (Unified Medical Language System) [7], MeSH (Medical Subject Heading) [8], Kingsbury Center for Cancer Care Glossary [9], MedicineNet Medical Dictionary [10], Multilingual Glossary of Technical, and Popular Medical Terms in nine European Languages [11], ICD (International Classification of Diseases) [12] among others [13]. Some ontologies are used in web retrieval systems [14], identification of relations between diseases [15], and diagnosis [16], among others [13]. Some ontologies are used in web retrieval systems [14], identification of relations between diseases [15], and diagnosis [16], among others.…”

Section: Introductionmentioning

confidence: 99%

“…Some ontologies are used in web retrieval systems [14], identification of relations between diseases [15], and diagnosis [16], among others [13]. Some ontologies are used in web retrieval systems [14], identification of relations between diseases [15], and diagnosis [16], among others. Uberon ontology is an anatomy ontology, which is a common standard used by the biomedical research community [17].…”

Section: Introductionmentioning

confidence: 99%

A histological ontology of the human cardiovascular system

et al. 2017

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BackgroundIn this paper, we describe a histological ontology of the human cardiovascular system developed in collaboration among histology experts and computer scientists.ResultsThe histological ontology is developed following an existing methodology using Conceptual Models (CMs) and validated using OOPS!, expert evaluation with CMs, and how accurately the ontology can answer the Competency Questions (CQ). It is publicly available at http://bioportal.bioontology.org/ontologies/HO and https://w3id.org/def/System.ConclusionsThe histological ontology is developed to support complex tasks, such as supporting teaching activities, medical practices, and bio-medical research or having natural language interactions.

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Creating Ontologies for Content Representation—The OntoSeed Suite

Bontas

Schlangen

Schräder

2005

Lecture Notes in Computer Science

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Abstract. Due to the inherent difficulties associated with manual ontology building, knowledge acquisition and reuse are often seen as methods that can make this tedious process easier. In this paper we present an NLP-based method to aid ontology design in a specific setting, namely that of semantic annotation of text. The method uses the World Wide Web in its analysis of the domain-specific documents, eliminating the need for linguistic knowledge and resources, and suggests ways to specify domain ontologies in a "linguistics-friendly" format in order to improve further ontology-based natural language processing tasks such as semantic annotation. We evaluate the method on a corpora in a real-world setting in the medical domain and compare the costs and the benefits of the NLP-based ontology engineering approach against a similar reuseoriented experiment.

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Generation and Management of a Medical Ontology in a Semantic Web Retrieval System

Cited by 12 publications

References 12 publications

Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues

Semantic Web in Healthcare: A Systematic Literature Review of Application, Research Gap, and Future Research Avenues

A histological ontology of the human cardiovascular system

Creating Ontologies for Content Representation—The OntoSeed Suite

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