A Complexity Measure for Clinical History Models

Authors

  • Antonio D'Uffizi IRPPS-CNR
  • Fabrizio L. Ricci IRPPS-CNR
  • Fabrizio Pecoraro IRPPS-CNR
  • Daniela Luzi IRPPS-CNR
  • Giuseppe Stecca IASI-CNR
  • Fabrizio Consorti Università Sapienza di Roma
  • Fabrizio Murgia

Abstract

Epidemiological transition needs a representation over time of a patient’s clinical history, which can be modelled by a customized Petri Net, the Health Issue Network exemplar (HINe) graph. Since HINe is used in a teaching/learning environment to model medical exercises, it is necessary to measure the exercise difficulty in order to assign them properly to learners of different level and ability. To this aim, the report describes the development of a new metrics for measuring the structural complexity of a HINe graph in order to compare different medical histories.

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Published

2023-11-21

How to Cite

D’Uffizi, A., Ricci, F. L., Pecoraro, F., Luzi, D., Stecca, G., Consorti, F., & Murgia, F. (2023). A Complexity Measure for Clinical History Models. IRPPS Working Papers, 1(1). Retrieved from http://epub.irpps.cnr.it/index.php/wp/article/view/293

Issue

IRPPS WPs pubblicati nel 2023

Section

Working Papers

License

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