program consists of 11 full papers
(in black), 6 position
papers (in red), one invited talk, and a
live system demonstrations (in
green). Full papers will have 15 minutes for
presentation followed by 5 minutes for questions. Position papers will
have 5 minutes for presentation without questions. System demostrations
will be in parallel.
Annette Ten Teije & David Riaño)
I: From Patient Data to Medical Ontologies (Chair: David Riaño)
|- David Sanchez and Antonio Moreno.
Creating Topic Hierarchies for Large Medical Libraries.
- Claudio Eccher, Andreas Seyfang, Antonella Ferro, Sergey Stankevich and Silvia Miksch. Bridging an Asbru Protocol to an Existing Electronic Patient Record.
- Maria Taboada, Maria Meizoso, David Riaño, Albert Alonso and Diego Martínez. From natural language descriptions in clinical guidelines to relationships in an ontology.
- Elena Cardillo, Andrei Tamilin and Luciano Serafini. A Hybrid Methodology for Consumer-oriented Healthcare Knowledge Acquisition.
- Krystyna Milian, Zharko Aleksovski, Richard Vdovjak, Annette ten Teije and Frank van Harmelen. Identifying Disease-Centric Subdomains in Very Large Medical Ontologies, a Case-Study on Breast-Cancer Concepts in SNOMED.
- Mor Peleg and Sagi Keren. The Knowledge-Data Ontology Mapper (KDOM): a Tool for Mapping Clinical Guidelines to EMRs.
||Session II: Temporal Reasoning (Chair: Annette Ten Teije)|
François Portet and Albert Gatt. Towards a Possibility-Theoretic
Approach to Uncertainty in Medical Data Interpretation and Text
- Feng Gao, Somayajulu Sripada, James Hunter and François Portet. Using Temporal Constraints to Detect Medical Events in the Neonatal ICU: A Demonstration.
Talk: Dr. Robert Stevens, The Changing Nature of Biomedical
Research: Semantic e-Science (Introduced
by David Riaño)
||Session III: Argumentation (Chair: Annette Ten Teije)|
Nikos Gorogiannis, Anthony Hunter, Vivek Patkar and Matthew Williams.
Argumentation about Treatment Efficacy.
- Mor Peleg and Daniel Rubin. Querying Radiology Appropriateness Criteria from a virtual Medical Record using GELLO.
||Session IV: Modelling Guidelines (Tools) (Chair: Mor Peleg)
Alessio Bottrighi, Federico Chesani, Paola Mello, Marco Montali, Paolo
Terenziani, Stefania Montani and Sergio Storari. Analysis of the GLARE
and GPROVE approaches to Clinical Guidelines.
- Ali Daniyal and Syed Sibte Raza Abidi. Semantic Web-based modeling of Clinical Pathways using the UML Activity Diagrams and OWL-S.
- Marco Rospocher, Claudio Eccher, Chiara Ghidini, Rakebul Hasan, Andreas Seyfang, Antonella Ferro and Silvia Miksch. CliP-MoKi: A collaborative tool for encoding Asbru Clinical Protocols.
- Erez Shalom, Avner Hatsek, Yuval Shahar and Galit Kaufman. System Demonstration: A Prototype for Automatic Application of A Guideline for Chronic Heart Failure Patients.
||Session V: Modelling Guidelines (Knowledge
Engineering) (Chair: Silvia
|- Maarten van der
Heijden and Peter Lucas. Extracting Qualitative Knowledge from Medical
Guidelines for Clinical Decision-Support Systems.
- Esther Lozano, Mar Marcos, Begoña Martínez-Salvador, Albert Alonso and J. Ramón Alonso. Experiences in the Development of Electronic Care Plans for the Management of Comorbidities.
- Francis Real and David Riaño. Toward the Merging of Clinical Algorithms.
||Live System Demostrations
Using Temporal Constraints to Detect Medical Events in the
Neonatal ICU: A Demonstration.
- The Knowledge-Data Ontology Mapper (KDOM): a Tool for Mapping Clinical Guidelines to EMRs.
- System Demonstration: A Prototype for Automatic Application of A Guideline for Chronic Heart Failure Patients.
- CliP-MoKi: A collaborative tool for encoding Asbru Clinical Protocols.
||Closing (by David
|Dr. Robert Stevens
Bio and Health Informatics Group
University of Manchester
The Changing Nature of Biomedical Research: Semantic e-Science
Biomedical science, like other sciences, is driven by observations. We wish to record these observations and how we made those observations. Such recording is a central part of the scientific process. Recently the life sciences have been producing observations (data or "facts") on an industrial scale. e-Science infra-structure is beginning to enable analysis on an industrial scale. The scientific process, however, requires both scientists and computers to share and communicate their facts and how these facts were generated (the protocols). In order to enable communication, both for humans and computers, we need common descriptions of facts, how these facts were produced and the ways in which these facts are analysed. Life science has begun to describe its data with terms supplied by ontologies. Life scientists are beginning to describe the semantics of their experiments (both wet and dry). The services that analyse these data are beginning to be semantically described. Semantic descriptions of services and data can come together with e-Science to give semantic e-Science that will afford many analytical opportunities for scientists. In this talk I will describe semantic science, e-Science and how these come together.
Robert Stevens is a senior lecturer in the BioHealth Informatics Group. His background in biochemistry, biological computation and computer science enables him to work at the interface between computer science and biology. Robert's main interest is in the computational representation of knowledge in ontologies and how this can be used to describe and analyse biological data. This is combined with the development and use of e-Science infra-structure.