Abstract
A key ability of human reasoning is analogical reasoning. In this context, an important notion is that of analogical proportions that have been formalized and analyzed in the last decade. A bridging to Formal Concept Analysis (FCA) has been brought by introducing analogical complexes, i.e. formal concepts that share a maximal analogical relation enabling by this analogies between (formal) concepts. Electronic Health Record (EHR) systems are nowadays widespread and used in different scenarios. In this paper we consider the problem of improving EHR systems by using analogical complexes in an FCA based setting. Moreover, we present a study case of analogical complexes in a medical field. We analyze analogical proportions in Electronic Health Record Systems and prove that EHRs can be improved with an FCA grounded analogical reasoning component. This component offers methods for knowledge discovery and knowledge acquisition for medical experts based on patterns revealed by analogies. We also show that combining analogical reasoning with FCA brings a new perspective on the analyzed data that can improve the understanding of the subsequent knowledge structures and offering a valuable support for decision making.
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Săcărea, C., Şotropa, D., Troancă, D. (2018). Using Analogical Complexes to Improve Human Reasoning and Decision Making in Electronic Health Record Systems. In: Chapman, P., Endres, D., Pernelle, N. (eds) Graph-Based Representation and Reasoning. ICCS 2018. Lecture Notes in Computer Science(), vol 10872. Springer, Cham. https://doi.org/10.1007/978-3-319-91379-7_2
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DOI: https://doi.org/10.1007/978-3-319-91379-7_2
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