Fifth Workshop on Case-Based Reasoning 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 Fifth Workshop on CBR in the Health Sciences

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

5. Summary • Application domaindialysis medicineeffects of fitness on dialysis • System contextISOR, a CBR system that explains the exceptional cases – those for which fitness does not improve renal function • Task / problem addressedrestoration of missing data • Research hypothesiscase-based reasoning can be applied to restore missing data in a dataset/case base • Main contributionsynergy between CBR and statistics (statistical modeling). Fifth Workshop on CBR in the Health Sciences

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7. A Case-Based Reasoning Approach to Dose Planning in Radiotherapy Xueyan Song1, Sanja Petrovic1, and Santhanam Sundar 2 1Automated Scheduling, Optimisation and Planning Group School of Computer Science University of Nottingham, UK 2Dept. of Oncology, City Hospital Campus, Nottingham University Hospitals NHS Trust, Nottingham, UK Fifth Workshop on CBR in the Health Sciences

8. Summary • Application domaindose planning in radiotherapy for prostate cancer • System contexttrade-off between the benefit in terms of cancer control and the risk in terms of harmful side effects to neighboring tissues • Task / problem addressedplanning problem – designing a radiotherapy dose planning • Research hypothesiscase-based reasoning can be applied to propose dose plans • Main contributionfuzzy representation of attribute values and similarity measurefusion of similar cases by Dempster-Shafer theory. Fifth Workshop on CBR in the Health Sciences

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10. On-Line Domain Knowledge Management forCase-Based Medical Recommendation Amélie Cordier1,Béatrice Fuchs1,Jean Lieber2, and Alain Mille1 1LIRIS 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 2LORIA (UMR 7503 CNRS–INRIA–Nancy Universities), BP 239, 54506 Vandoeuvre-lès-Nancy, France Jean.Lieber@loria.fr Fifth Workshop on CBR in the Health Sciences

11. Summary • Application domainbreast cancer treatment • System contextKasimir is a knowledge management and decision-support system in oncology focusing on case-based protocol treatment recommendations • Task / problem addressedplanning problem – recommending a treatment plan based on a protocol • Research hypothesesconservative adaptation is recommended for adapting a protocol to a new case through case-based reasoningnew domain knowledge can be acquired by analysis of failures • Main contributionimprovement of adaptationmethod for learning from failures of the case-based reasoning. Fifth Workshop on CBR in the Health Sciences

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

14. Summary • Application domainHep-2 cell image interpretation • System contextcase-based image interpretation • Task / problem addressedclassification problem – improve recognition of over 30 different nuclear and cytoplasmic patterns when patterns change over time or new patterns emerge • Research hypothesiscase-based reasoning can be applied to the problem of novelty detection and also of concept drift • Main contributionnovel application for CBR: detecting novelty, detecting concept drift. Fifth Workshop on CBR in the Health Sciences

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

17. Summary • Application domainany medical domain • System contextelectronic medical records • Task / problem addressedretrieval task – finding similar cases represented with structured and semi-structured data • Research hypothesisa hybrid similarity measure based on combining the cosine similarity measure, an ontology, and the nearest neighbor method permit to successfully retrieve similar cases • Main contributionsynergy between case-based reasoning and information retrieval. Fifth Workshop on CBR in the Health Sciences

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19. Towards Case-Based Reasoning for DiabetesManagement Cindy Marling1, Jay Shubrook2 and Frank Schwartz2 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 Fifth Workshop on CBR in the Health Sciences

20. Summary • Application domaintype I diabetes management • System contextreal-time monitoring of glucose level through insulin pump • Task / problem addressedtreatment planning – adjusting insulin dosage • Research hypothesiscase-based reasoning can adjust insulin dosage in real timecases required for the future CBR system can be acquired through an online Web-based interface • Main contributionplanning the development of a case-based reasoning system for automatic type I diabetes monitoring. 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 Fifth Workshop on CBR in the Health Sciences

22. Summary • Application domaincontact lenses classification • System contextconversational CBR • Task / problem addressedclassification problem – recommending type of contact lenses • Research hypothesisa 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 contributionsynergy between case-based reasoning and hypothetico-deductive reasoningexplanations in CBR. Fifth Workshop on CBR in the Health Sciences

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24. Other Papers Summaries • Case-based Reasoning for managing non-compliance with clinical guidelines, Stefania Montani, University of Piemonte Orientale, Alessandria, ItalyA 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, ItalyA CBR system able to choose the appropriate parameters for the configuration of temporal abstractions in medical domain of haemodyalisis Fifth Workshop on CBR in the Health Sciences

25. Other Papers Summaries • Prototypical Cases for Knowledge Maintenance in Biomedical CBR, Isabelle Bichindaritz, University of Washington, Tacoma, WA, USAPrototypical 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 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) 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 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.orghttp://www.cbr-biomed.org Fifth Workshop on CBR in the Health Sciences

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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 ! Fifth Workshop on CBR in the Health Sciences