Fifth Workshop on Case-Based Reasoning in the Health Sciences Isabelle Bichindaritz



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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


Workshop Stats

  • Papers accepted: 10 papers

  • Attendees: 19 participants

  • Good news !!!



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



A CBR Solution for Missing Medical Data



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).







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.





On-Line Domain Knowledge Management for Case-Based Medical Recommendation



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.





Concepts for Novelty Detection and Handling based on Case-Based Reasoning



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.





Similarity of Medical Cases in Health Care Using Cosine Similarity and Ontology



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.





Towards Case-Based Reasoning for Diabetes Management



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.



Hypothetico-Deductive Case-Based Reasoning



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.





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



Other Papers Summaries

  • 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



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)


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


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







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 !



Каталог: davils -> iccbr07ws


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