Ontology Based Disease Information System

Thirugnanam, Mythili; Ramaiah, Mangayarkarasi; Pattabiraman, V.; Sivakumar, R.

doi:10.1016/j.proeng.2012.06.375

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…Thirugnanam, Ramaiah, and Sivakumar [45] present a disease information system that provides a diagnosis on the basis of symptoms. A formal OWL ontology models system-wise diseases (circulatory and digestive) and their symptoms.…”

Section: Domain Knowledge Representationmentioning

confidence: 99%

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Formal Ontologies in Information Systems Development: A Systematic Review

Husáková

Bureš

2020

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Computational ontologies are machine-processable structures which represent particular domains of interest. They integrate knowledge which can be used by humans or machines for decision making and problem solving. The main aim of this systematic review is to investigate the role of formal ontologies in information systems development, i.e., how these graphs-based structures can be beneficial during the analysis and design of the information systems. Specific online databases were used to identify studies focused on the interconnections between ontologies and systems engineering. One-hundred eighty-seven studies were found during the first phase of the investigation. Twenty-seven studies were examined after the elimination of duplicate and irrelevant documents. Mind mapping was substantially helpful in organising the basic ideas and in identifying five thematic groups that show the main roles of formal ontologies in information systems development. Formal ontologies are mainly used in the interoperability of information systems, human resource management, domain knowledge representation, the involvement of semantics in unified modelling language (UML)-based modelling, and the management of programming code and documentation. We explain the main ideas in the reviewed studies and suggest possible extensions to this research.

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Section: Domain Knowledge Representationmentioning

confidence: 99%

“…The systematic review identified several applications of formal ontologies in medicine, especially for the diagnoses of specific diseases. An inference mechanism can use an ontology and formal rules for the diagnosis of the system-wise diseases [45].…”

Section: Contribution Of Ontologies In Information Systems Development and Future Directionsmentioning

confidence: 99%

Formal Ontologies in Information Systems Development: A Systematic Review

Husáková

Bureš

2020

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“…They presented a system to monitor the vital signs of patients who receive medical treatment in homecare environments. An ontology-based disease information system was developed by Thirugnanam et al (2012). This system consists of three phases: knowledge acquisition and ontology creation phase, rule engine phase and query processing phase.…”

Section: Introductionmentioning

confidence: 99%

Ontology based Baysian network for clinical specialty supporting in interactive question answering systems

Yeh

Huang

2017

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Purpose This study aims to provide an ontology based Baysian network for clinical specialty supporting. As a knowledge base, ontology plays an essential role in domain applications especially in expert systems. Interactive question answering systems are suitable for personal domain consulting and recommended for real-time usage. Clinical specialty supporting for dispatching patients can assist hospitals to locate desired treatment departments for individuals relevant to their syndromes and disease efficiently and effectively. By referring to interactive question answering systems, individuals can understand how to alleviate time and medical resource wasting according to recommendations from medical ontology-based systems. Design/methodology/approach This work presents an ontology based on clinical specialty supporting using an interactive question answering system to achieve this aim. The ontology incorporates close temporal associations between words in input query to represent word co-occurrence relationships in concept space. The patterns defined in lexicon chain mechanism are further extracted from the query words to infer related concepts for treatment departments to retrieve information. Findings The precision and recall rates are considered as the criteria for model optimization. Finally, the inference-based interactive question answering system using natural language interface is adopted for clinical specialty supporting, and indicates its superiority in information retrieval over traditional approaches. Originality/value From the observed experimental results, we find the proposed method is useful in practice especially in treatment department decision supporting using metrics precision and recall rates. The interactive interface using natural language dialogue attracts the users’ attention and obtains a good score in mean opinion score measure.

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“…On the other hand, human body systems consist of specific cells, tissues, and organs that work together to perform specific functions. Conceptually, these systems are interconnected and dependent, so they can't work separately, such as (Nervous System, Respiratory System, Immune System, Digestive System and Hepatobiliary System) [16,17]. The Hepatobiliary system includes four organs (Liver, Gallbladder, Bile duct and Pancreas).…”

Section: Introductionmentioning

confidence: 99%

Ontology-based Approach for Hepatobiliary System Diseases

Marzoqi¹,

Alfonse²,

Moawad³

et al. 2016

IJe-HIS

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Medical Ontologies play a central role in integrating heterogeneous databases of various model organisms. The Hepatobiliary system is very important for human vital processes. It has an ability to regulate the other systems. Furthermore, it plays an important role in many body functions like protein production. Also, it may be affected by many pathologic conditions, which affect other organs negatively.. This paper investigates the current studies on Ontology-based approach and Ontology techniques for Hepatobiliary System Diseases. We present conceptual view for the Hepatobiliary system and its infected diseases. Besides, we propose a new classification schema for the research efforts investigated so far. We classified the research efforts investigated so far based on the Hepatobiliary system organs: Liver, Gallbladder, Bile duct and Pancreas. Besides, we discuss the current research gaps found in this research area.

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Ontology Based Disease Information System

Cited by 9 publications

References 13 publications

Formal Ontologies in Information Systems Development: A Systematic Review

Formal Ontologies in Information Systems Development: A Systematic Review

Ontology based Baysian network for clinical specialty supporting in interactive question answering systems

Ontology-based Approach for Hepatobiliary System Diseases

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