Towards an ontology-driven clinical experience sharing ecosystem: Demonstration with liver cases

Mar\'\ia del Mar Rold\'an-Garc\'\ia, Suzan Uskudarli, Neda B Marvasti, Burak Acar, Jos\'e F Aldana-Montes

Expert Systems with Applications

Abstract

Past medical cases, hence clinical experience, are invaluable resources in supporting clinical practice, research, and education. Medical professionals need to be able to exchange information about patient cases and explore them from subjective perspectives. This requires a systematic and flexible methodology to case representation for supporting the exchange of processable patient information. We present an ontology based approach to modeling patient cases and use patients with liver disease conditions as an example. To this end a novel ontology, lico, that utilizes well known medical standards is proposed to represent liver patient cases. The utility of the proposed approach is demonstrated with semantic queries and reasoning using data collected from real patients. The preliminary results are promising in regards to the potentials of ontology based medical case representation for building case-based search and retrieval systems, paving the way towards a Clinical Experience Sharing platform for comparative diagnosis, research, and education.

BibTeX

@article{del2018towards,
  title        = {Towards an ontology-driven clinical experience sharing ecosystem: Demonstration with liver cases},
  author       = {del Mar Rold{\'a}n-Garc{\'\i}a, Mar{\'\i}a and Uskudarli, Suzan and Marvasti, Neda B and Acar, Burak and Aldana-Montes, Jos{\'e} F},
  year         = 2018,
  journal      = {Expert Systems with Applications},
  publisher    = {Elsevier},
  volume       = 101,
  pages        = {176--195},
  doi          = {10.1016/j.eswa.2018.02.001},
  link         = {https://www.sciencedirect.com/science/article/abs/pii/S095741741830071X},
  abstract     = {Past medical cases, hence clinical experience, are invaluable resources in supporting clinical practice, research, and education. Medical professionals need to be able to exchange information about patient cases and explore them from subjective perspectives. This requires a systematic and flexible methodology to case representation for supporting the exchange of processable patient information. We present an ontology based approach to modeling patient cases and use patients with liver disease conditions as an example. To this end a novel ontology, lico, that utilizes well known medical standards is proposed to represent liver patient cases. The utility of the proposed approach is demonstrated with semantic queries and reasoning using data collected from real patients. The preliminary results are promising in regards to the potentials of ontology based medical case representation for building case-based search and retrieval systems, paving the way towards a Clinical Experience Sharing platform for comparative diagnosis, research, and education.},
  group        = {journal}
}