An architecture for semantic navigation and reasoning with patient data - experiences of the Health-e-Child project
Description
Medical ontologies have become the standard means of recording and accessing conceptualized biological and medical knowledge. The expressivity of these ontologies goes from simple concept lists through taxonomies to formal logical theories. In the context of patient information, their application is primarily annotation of medical (instance) data. To exploit higher expressivity, we propose an architecture which allows for reasoning on patient data using OWL DL ontologies. The implementation is carried out as part of the Health-e-Child platform prototype. We discuss the use case where ontologies establish a hierarchical classification of patients which in turn is used to aid the visualization of patient data. We briefly discuss the treemap-based patient viewer which has been evaluated in the Health-e-Child project.
| Slides | |
| 0:00 | An Architecture for Semantic Navigation and Reasoning with Patient Data |
| 0:09 | Credits |
| 0:28 | Analyzing a Neuro-oncology Patient Set |
| 2:16 | Outline |
| 3:26 | Introduction |
| 6:32 | Reasoning and Visualization –shopping list |
| 8:05 | Visualization Requirements |
| 8:42 | Medical Ontologies |
| 10:23 | Our running example |
| 11:19 | Logical Theory |
| 13:49 | Meronomy in FMA induces Patient Taxonomy |
| 14:34 | Patient Classification with Reasoning |
| 15:17 | System Architecture |
| 16:51 | Creation of DL views |
| 17:38 | Visualization |
| 18:14 | Treemap browser in HeC |
| 19:27 | Patient Data Visualization using TreeMaps |
| 21:59 | Visual Data Mining |
| 22:59 | Conclusions |
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