Analysis and visualization of disease courses in a semantically-enabled cancer registry
Abstract Background Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays. However, the lack of a well-defined common seman...
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| Format: | Article |
| Language: | English |
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BMC
2017-09-01
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| Series: | Journal of Biomedical Semantics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13326-017-0154-9 |
| _version_ | 1818339568019046400 |
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| author | Angel Esteban-Gil Jesualdo Tomás Fernández-Breis Martin Boeker |
| author_facet | Angel Esteban-Gil Jesualdo Tomás Fernández-Breis Martin Boeker |
| author_sort | Angel Esteban-Gil |
| collection | DOAJ |
| description | Abstract Background Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays. However, the lack of a well-defined common semantic model is a problem when user-defined analyses and data linking to external resources are required. The objectives of this study are: (1) design of a semantic model for local cancer registries; (2) development of a semantically-enabled cancer registry based on this model; and (3) semantic exploitation of the cancer registry for analysing and visualising disease courses. Results Our proposal is based on our previous results and experience working with semantic technologies. Data stored in a cancer registry database were transformed into RDF employing a process driven by OWL ontologies. The semantic representation of the data was then processed to extract semantic patient profiles, which were exploited by means of SPARQL queries to identify groups of similar patients and to analyse the disease timelines of patients. Based on the requirements analysis, we have produced a draft of an ontology that models the semantics of a local cancer registry in a pragmatic extensible way. We have implemented a Semantic Web platform that allows transforming and storing data from cancer registries in RDF. This platform also permits users to formulate incremental user-defined queries through a graphical user interface. The query results can be displayed in several customisable ways. The complex disease timelines of individual patients can be clearly represented. Different events, e.g. different therapies and disease courses, are presented according to their temporal and causal relations. Conclusion The presented platform is an example of the parallel development of ontologies and applications that take advantage of semantic web technologies in the medical field. The semantic structure of the representation renders it easy to analyse key figures of the patients and their evolution at different granularity levels. |
| first_indexed | 2024-12-13T15:29:04Z |
| format | Article |
| id | doaj.art-74228c420f5b4bad821e180e99acd23a |
| institution | Directory Open Access Journal |
| issn | 2041-1480 |
| language | English |
| last_indexed | 2024-12-13T15:29:04Z |
| publishDate | 2017-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Semantics |
| spelling | doaj.art-74228c420f5b4bad821e180e99acd23a2022-12-21T23:40:15ZengBMCJournal of Biomedical Semantics2041-14802017-09-018111610.1186/s13326-017-0154-9Analysis and visualization of disease courses in a semantically-enabled cancer registryAngel Esteban-Gil0Jesualdo Tomás Fernández-Breis1Martin Boeker2Fundación para la Formación e Investigación Sanitarias de la Región de Murcia, Biomedical Informatics & Bioinformatics PlatformDpto. Informática y Sistemas, Facultad de Informática, Universidad de MurciaInstitute for Medical Biometry and Statistics, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgAbstract Background Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays. However, the lack of a well-defined common semantic model is a problem when user-defined analyses and data linking to external resources are required. The objectives of this study are: (1) design of a semantic model for local cancer registries; (2) development of a semantically-enabled cancer registry based on this model; and (3) semantic exploitation of the cancer registry for analysing and visualising disease courses. Results Our proposal is based on our previous results and experience working with semantic technologies. Data stored in a cancer registry database were transformed into RDF employing a process driven by OWL ontologies. The semantic representation of the data was then processed to extract semantic patient profiles, which were exploited by means of SPARQL queries to identify groups of similar patients and to analyse the disease timelines of patients. Based on the requirements analysis, we have produced a draft of an ontology that models the semantics of a local cancer registry in a pragmatic extensible way. We have implemented a Semantic Web platform that allows transforming and storing data from cancer registries in RDF. This platform also permits users to formulate incremental user-defined queries through a graphical user interface. The query results can be displayed in several customisable ways. The complex disease timelines of individual patients can be clearly represented. Different events, e.g. different therapies and disease courses, are presented according to their temporal and causal relations. Conclusion The presented platform is an example of the parallel development of ontologies and applications that take advantage of semantic web technologies in the medical field. The semantic structure of the representation renders it easy to analyse key figures of the patients and their evolution at different granularity levels.http://link.springer.com/article/10.1186/s13326-017-0154-9Biomedical informaticsSemantic webCancer registryOntology |
| spellingShingle | Angel Esteban-Gil Jesualdo Tomás Fernández-Breis Martin Boeker Analysis and visualization of disease courses in a semantically-enabled cancer registry Journal of Biomedical Semantics Biomedical informatics Semantic web Cancer registry Ontology |
| title | Analysis and visualization of disease courses in a semantically-enabled cancer registry |
| title_full | Analysis and visualization of disease courses in a semantically-enabled cancer registry |
| title_fullStr | Analysis and visualization of disease courses in a semantically-enabled cancer registry |
| title_full_unstemmed | Analysis and visualization of disease courses in a semantically-enabled cancer registry |
| title_short | Analysis and visualization of disease courses in a semantically-enabled cancer registry |
| title_sort | analysis and visualization of disease courses in a semantically enabled cancer registry |
| topic | Biomedical informatics Semantic web Cancer registry Ontology |
| url | http://link.springer.com/article/10.1186/s13326-017-0154-9 |
| work_keys_str_mv | AT angelestebangil analysisandvisualizationofdiseasecoursesinasemanticallyenabledcancerregistry AT jesualdotomasfernandezbreis analysisandvisualizationofdiseasecoursesinasemanticallyenabledcancerregistry AT martinboeker analysisandvisualizationofdiseasecoursesinasemanticallyenabledcancerregistry |