Publicação
Visualising time-evolving semantic biomedical data
| Resumo: | Today, medical studies enable a deeper understanding of health conditions, diseases and treatments, helping to improve medical care services. In observational studies, an adequate selection of datasets is important, to ensure the study's success and the quality of the results obtained. During the feasibility study phase, inclusion and exclusion criteria are defined, together with specific database characteristics to construct the cohort. However, it is not easy to compare database characteristics and their evolution over time during this selection. Data comparisons can be made using the data properties and aggregations, but the inclusion of temporal information becomes more complex due to the continuous evolution of concepts over time. In this paper, we propose two visualisation methods aiming for a better description of data evolution in clinical registers using biomedical standard vocabularies. |
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| Autores principais: | Pereira, Arnaldo |
| Outros Autores: | Rafael Almeida, Joao; Lopes, Rui Pedro; Oliveira, José Luís |
| Assunto: | Biomedical data Temporal data Data visualisation Evidence-based medicine Ontology evolution |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | português |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | Today, medical studies enable a deeper understanding of health conditions, diseases and treatments, helping to improve medical care services. In observational studies, an adequate selection of datasets is important, to ensure the study's success and the quality of the results obtained. During the feasibility study phase, inclusion and exclusion criteria are defined, together with specific database characteristics to construct the cohort. However, it is not easy to compare database characteristics and their evolution over time during this selection. Data comparisons can be made using the data properties and aggregations, but the inclusion of temporal information becomes more complex due to the continuous evolution of concepts over time. In this paper, we propose two visualisation methods aiming for a better description of data evolution in clinical registers using biomedical standard vocabularies. |
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