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A Knowledge Evocation Model in Grading Healthcare Institutions Using Rough Set and Formal Concept Analysis

  • Arati Mohapatro
  • S. K. Mahendran
  • T. K. DasEmail author
Conference paper
  • 12 Downloads
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 127)

Abstract

A comparison of healthcare institutions by ranking involves generating their relative scores based on infrastructure, process, services and other quality dynamics. Being a top-ranking institute depends on the overall score secured against the hospital quality parameters that are being assessed for ranking. However, each of the parameters does not equally important when it comes ranking. Hence, the objective of this research is to explore the parameters which are vital one as they significantly influence the ranking score. In this paper, a hybrid model is presented for knowledge extraction, which employs techniques of rough set on intuitionistic fuzzy approximation space (RSIFAS) for classification, Learning from Examples Module 2 (LEM2) algorithm for generating decision rules and formal concept analysis (FCA) for attribute exploration. The model can be implemented using a ranking scored data for any of the specialisations (cancer, heart disease, etc.). The result would signify the connection between quality attributes and ranking.

Keywords

Rough set with intuitionistic fuzzy approximation space Formal concept analysis Hospital ranking Knowledge mining Attribute exploration 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Bharathiar UniversityCoimbatoreIndia
  2. 2.Department of Computer ScienceGovernment Arts CollegeUdhagamandalamIndia
  3. 3.SITEVellore Institute of TechnologyVelloreIndia

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