1. Fifth Workshop on CBR in the Health Sciences 1 Fifth Workshop on Case- Based Reasoning in the Health Sciences Isabelle Bichindaritz University of Washington, Tacoma, Washington, USA ibichind@u.washington.edu Stefania Montani University of Piemonte Orientale, Italy stefania.montani@unipmn.it

2. Fifth Workshop on CBR in the Health Sciences 2 Workshop Stats Papers accepted: 10 papers Attendees: 19 participants Good news !!!

3. Fifth Workshop on CBR in the Health Sciences 3 Workshop Goals Provide a forum for identifying important contributions and opportunities for research on the application of CBR to the Health Sciences Promote the systematic study of how to apply CBR to the Health Sciences Showcase applications of CBR in the Health Sciences

4. Fifth Workshop on CBR in the Health Sciences 4 A CBR Solution for Missing Medical Data Olga Vorobieva and Rainer Schmidt Institute for Medical Informatics and Biometry University of Rostock, Germany Alexander Rumiantzev Pavlov State Medical University, St.Petersburg, Russia

5. Fifth Workshop on CBR in the Health Sciences 5 Summary Application domain dialysis medicine effects of fitness on dialysis System context ISOR, a CBR system that explains the exceptional cases – those for which fitness does not improve renal function Task / problem addressed restoration of missing data Research hypothesis case-based reasoning can be applied to restore missing data in a dataset/case base Main contribution synergy between CBR and statistics (statistical modeling).

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7. 7 A Case-Based Reasoning Approach to Dose Planning in Radiotherapy Xueyan Song 1, Sanja Petrovic 1, and Santhanam Sundar 2 1 Automated Scheduling, Optimisation and Planning Group School of Computer Science University of Nottingham, UK 2 Dept. of Oncology, City Hospital Campus, Nottingham University Hospitals NHS Trust, Nottingham, UK

8. Fifth Workshop on CBR in the Health Sciences 8 Summary Application domain dose planning in radiotherapy for prostate cancer System context trade-off between the benefit in terms of cancer control and the risk in terms of harmful side effects to neighboring tissues Task / problem addressed planning problem – designing a radiotherapy dose planning Research hypothesis case-based reasoning can be applied to propose dose plans Main contribution fuzzy representation of attribute values and similarity measure fusion of similar cases by Dempster-Shafer theory.

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10. 10 On-Line Domain Knowledge Management for Case-Based Medical Recommendation Amélie Cordier 1,Béatrice Fuchs 1,Jean Lieber 2, and Alain Mille 1 1 LIRIS CNRS, UMR 5202, Université Lyon 1, INSA Lyon, Université Lyon 2, ECL 43, bd du 11 Novembre 1918, Villeurbanne Cedex, France, {Amelie.Cordier, Beatrice.Fuchs, Alain.Mille}@liris.cnrs.fr 2 LORIA (UMR 7503 CNRS–INRIA–Nancy Universities), BP 239, 54506 Vandoeuvre-lès-Nancy, France Jean.Lieber@loria.fr

11. Fifth Workshop on CBR in the Health Sciences 11 Summary Application domain breast cancer treatment System context Kasimir is a knowledge management and decision-support system in oncology focusing on case-based protocol treatment recommendations Task / problem addressed planning problem – recommending a treatment plan based on a protocol Research hypotheses conservative adaptation is recommended for adapting a protocol to a new case through case-based reasoning new domain knowledge can be acquired by analysis of failures Main contribution improvement of adaptation method for learning from failures of the case-based reasoning.

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13. Fifth Workshop on CBR in the Health Sciences 13 Concepts for Novelty Detection and Handling based on Case-Based Reasoning Petra Perner Institute of Computer Vision and applied Computer Sciences, IBaI

14. Fifth Workshop on CBR in the Health Sciences 14 Summary Application domain Hep-2 cell image interpretation System context case-based image interpretation Task / problem addressed classification problem – improve recognition of over 30 different nuclear and cytoplasmic patterns when patterns change over time or new patterns emerge Research hypothesis case-based reasoning can be applied to the problem of novelty detection and also of concept drift Main contribution novel application for CBR: detecting novelty, detecting concept drift.

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16. Fifth Workshop on CBR in the Health Sciences 16 Similarity of Medical Cases in Health Care Using Cosine Similarity and Ontology Shahina Begum, Mobyen Uddin Ahmed, Peter Funk, Ning Xiong, Bo von Schéele Mälardalen University, Department of Computer Science and Electronics PO Box 883 SE-721 23, Västerås, Sweden {firstname.lastname}@mdh.se

17. Fifth Workshop on CBR in the Health Sciences 17 Summary Application domain any medical domain System context electronic medical records Task / problem addressed retrieval task – finding similar cases represented with structured and semi-structured data Research hypothesis a hybrid similarity measure based on combining the cosine similarity measure, an ontology, and the nearest neighbor method permit to successfully retrieve similar cases Main contribution synergy between case-based reasoning and information retrieval.

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19. Fifth Workshop on CBR in the Health Sciences 19 Towards Case-Based Reasoning for Diabetes Management Cindy Marling 1, Jay Shubrook 2 and Frank Schwartz 2 1 School of Electrical Engineering and Computer Science Russ College of Engineering and Technology Ohio University, Athens, Ohio 45701, USA marling@ohio.edu 2 Appalachian Rural Health Institute, Diabetes and Endocrine Center College of Osteopathic Medicine Ohio University, Athens, Ohio 45701, USA shubrook@ohio.edu, schwartf@ohio.edu

20. Fifth Workshop on CBR in the Health Sciences 20 Summary Application domain type I diabetes management System context real-time monitoring of glucose level through insulin pump Task / problem addressed treatment planning – adjusting insulin dosage Research hypothesis case-based reasoning can adjust insulin dosage in real time cases required for the future CBR system can be acquired through an online Web-based interface Main contribution planning the development of a case-based reasoning system for automatic type I diabetes monitoring.

21. Fifth Workshop on CBR in the Health Sciences 21 Hypothetico-Deductive Case-Based Reasoning David McSherry School of Computing and Information Engineering, University of Ulster, Northern Ireland

22. Fifth Workshop on CBR in the Health Sciences 22 Summary Application domain contact lenses classification System context conversational CBR Task / problem addressed classification problem – recommending type of contact lenses Research hypothesis a hypothetico-deductive CBR approach to test selection can minimize the number of tests required to confirm a hypothesis proposed by the system or user Main contribution synergy between case-based reasoning and hypothetico- deductive reasoning explanations in CBR.

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24. Fifth Workshop on CBR in the Health Sciences 24 Other Papers Summaries Case-based Reasoning for managing non- compliance with clinical guidelines, Stefania Montani, University of Piemonte Orientale, Alessandria, Italy A CBR system able to –Retrieve similar past episodes (cases) of non-compliance to guidelines, to be suggested to the physician –Learn more general indications from ground non-compliance cases, adoptable for a formal GL revision by an experts committee CBR for Temporal Abstractions Configuration in Haemodyalisis, Leonardi Giorgio, Bottrighi Alessio, Portinale Luigi, Montani Stefania, University of Piemonte Orientale, Alessandria, Italy A CBR system able to choose the appropriate parameters for the configuration of temporal abstractions in medical domain of haemodyalisis

25. Fifth Workshop on CBR in the Health Sciences 25 Other Papers Summaries Prototypical Cases for Knowledge Maintenance in Biomedical CBR,Prototypical Cases for Knowledge Maintenance in Biomedical CBR, Isabelle Bichindaritz, University of Washington, Tacoma, WA, USA Prototypical cases have served various purposes in biomedical CBR systems, among which to organize and structure the memory, to guide the retrieval as well as the reuse of cases, and to serve as bootstrapping a CBR system memory when real cases are not available in sufficient quantity and/or quality. Knowledge maintenance is yet another role that these prototypical cases can play in biomedical CBR systems

26. Fifth Workshop on CBR in the Health Sciences 26 Discussion Trends and issues –Integration of CBR with electronic patient records and/or in clinical practice (Begum et al., Marling et al.) –Importance of prototypical cases (Bichindaritz) –Incompleteness / non-reliability of cases or CBR system knowledge (Vorobieva et al., Cordier et al., Bichindaritz) –Novel domains of applications for CBR (Perner, Leonardi et al., Montani) –Need for synergy with other AI methods (Song et al., McSherry)

27. Fifth Workshop on CBR in the Health Sciences 27 Discussion Pearls of wisdom –Remember Occam’s razor – introducing complexity in CBR should be carefully justified –Knowledge in medical cases / domain knowledge is often questionable – finding methods for dealing with this reality is essential for the development of CBR in biomedical domains –CBR can be promoted as the methodology of choice for evidence gathering in evidence-based medicine

28. Fifth Workshop on CBR in the Health Sciences 28 Future Plans A second special issue on CBR in the Health Sciences, based on papers from this Fifth Workshop on CBR in the Health Sciences is going to be published in Computational Intelligence. The Web-site (version 1.beta) and mailing list for our research group are now live: http://www.cbr-health.org http://www.cbr-biomed.org http://www.cbr-health.org http://www.cbr-biomed.org

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31. Fifth Workshop on CBR in the Health Sciences 31 Future Plans A book on CBR in the Health Sciences is in preparation. Please contact us should you want to contribute – we may also contact you !