A reference ontology for biomedical informatics: the foundational model of anatomy
Journal of Biomedical Informatics - Special issue: Unified medical language system
GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines
Journal of Biomedical Informatics
Methods in biomedical ontology
Journal of Biomedical Informatics - Special issue: Biomedical ontologies
A taxonomic description of computer-based clinical decision support systems
Journal of Biomedical Informatics
The SDA Model: A Set Theory Approach
CBMS '07 Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems
Grand challenges in clinical decision support
Journal of Biomedical Informatics
An ontological knowledge framework for adaptive medical workflow
Journal of Biomedical Informatics
Towards the Merging of Multiple Clinical Protocols and Guidelines via Ontology-Driven Modeling
AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
Home Care Personalisation with Individual Intervention Plans
Knowledge Management for Health Care Procedures
Journal of Biomedical Informatics
Guest editorial: special section on personal health systems
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Ontology-based retrospective and prospective diagnosis and medical knowledge personalization
KR4HC'10 Proceedings of the ECAI 2010 conference on Knowledge representation for health-care
Journal of Biomedical Informatics
Cross-product extensions of the Gene Ontology
Journal of Biomedical Informatics
Detecting dominant alternative interventions to reduce treatment costs
KR4HC'11 Proceedings of the 3rd international conference on Knowledge Representation for Health-Care
Dynamic multi-version ontology-based personalization
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Journal of Biomedical Informatics
Adapting domain ontology for personalized knowledge search and recommendation
Information and Management
Methodological Review: Computer-interpretable clinical guidelines: A methodological review
Journal of Biomedical Informatics
Data & Knowledge Engineering
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Chronically ill patients are complex health care cases that require the coordinated interaction of multiple professionals. A correct intervention of these sort of patients entails the accurate analysis of the conditions of each concrete patient and the adaptation of evidence-based standard intervention plans to these conditions. There are some other clinical circumstances such as wrong diagnoses, unobserved comorbidities, missing information, unobserved related diseases or prevention, whose detection depends on the capacities of deduction of the professionals involved. In this paper, we introduce an ontology for the care of chronically ill patients and implement two personalization processes and a decision support tool. The first personalization process adapts the contents of the ontology to the particularities observed in the health-care record of a given concrete patient, automatically providing a personalized ontology containing only the clinical information that is relevant for health-care professionals to manage that patient. The second personalization process uses the personalized ontology of a patient to automatically transform intervention plans describing health-care general treatments into individual intervention plans. For comorbid patients, this process concludes with the semi-automatic integration of several individual plans into a single personalized plan. Finally, the ontology is also used as the knowledge base of a decision support tool that helps health-care professionals to detect anomalous circumstances such as wrong diagnoses, unobserved comorbidities, missing information, unobserved related diseases, or preventive actions. Seven health-care centers participating in the K4CARE project, together with the group SAGESA and the Local Health System in the town of Pollenza have served as the validation platform for these two processes and tool. Health-care professionals participating in the evaluation agree about the average quality 84% (5.9/7.0) and utility 90% (6.3/7.0) of the tools and also about the correct reasoning of the decision support tool, according to clinical standards.