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A logic-based decision support system for the diagnosis of headache disorders according to the ICHD-3 international classification

Published online by Cambridge University Press:  22 September 2020

ROBERTA COSTABILE Open the ORCID record for ROBERTA COSTABILE [Opens in a new window] ,
GELSOMINA CATALANO ,
BERNARDO CUTERI Open the ORCID record for BERNARDO CUTERI [Opens in a new window] ,
MARIA CONCETTA MORELLI ,
NICOLA LEONE  and
MARCO MANNA Open the ORCID record for MARCO MANNA [Opens in a new window]
ROBERTA COSTABILE
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: r.costabile@mat.unical.it)
GELSOMINA CATALANO
Affiliation:
DLVSystem Srl, Rende, Italy (e-mail: catalano@dlvsystem.com)
BERNARDO CUTERI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: cuteri@mat.unical.it)
MARIA CONCETTA MORELLI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: maria.morelli@unical.it)
NICOLA LEONE
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: leone@mat.unical.it, manna@mat.unical.it)
MARCO MANNA
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: leone@mat.unical.it, manna@mat.unical.it)
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Abstract

Decision support systems play an important role in medical fields as they can augment clinicians to deal more efficiently and effectively with complex decision-making processes. In the diagnosis of headache disorders, however, existing approaches and tools are still not optimal. On the one hand, to support the diagnosis of this complex and vast spectrum of disorders, the International Headache Society released in 1988 the International Classification of Headache Disorders (ICHD), now in its 3rd edition: a 200 pages document classifying more than 300 different kinds of headaches, where each is identified via a collection of specific nontrivial diagnostic criteria. On the other hand, the high number of headache disorders and their complex criteria make the medical history process inaccurate and not exhaustive both for clinicians and existing automatic tools. To fill this gap, we present head-asp, a novel decision support system for the diagnosis of headache disorders. Through a REST Web Service, head-asp implements a dynamic questionnaire that complies with ICHD-3 by exploiting two logical modules to reach a complete diagnosis while trying to minimize the total number of questions being posed to patients. Finally, head-asp is freely available on-line and it is receiving very positive feedback from the group of neurologists that is testing it.

Keywords

Knowledge RepresentationASPArtificial IntelligenceICHD-3
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 20 , Issue 6: 36th International Conference on Logic Programming Special Issue II , November 2020 , pp. 864 - 879
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Copyright
© The Author(s), 2020. Published by Cambridge University Press

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Footnotes

*

This work has been partially supported by MISE under the project “ALCMEONE” (NUM:F/050502/01-02-03/X32, CUP:B28117000430008) – Horizon 2020 PON 2014-2020.

References

Alviano, M., Calimeri, F., Dodaro, C., Fuscà, D., Leone, N., Perri, S., Ricca, F., Veltri, P., and Zangari, J. 2017. The ASP system DLV2. In Proc. of LPNMR’17. 215–221.Google Scholar
Calimeri, F., Faber, W., Gebser, M., Ianni, G., Kaminski, R., Krennwallner, T., Leone, N., Maratea, M., Ricca, F., and Schaub, T. 2020. ASP-Core-2 input language format. Theory Pract. Log. Program. 20, 2, 294–309.Google Scholar
De Simone, R., Marano, E., and Bonavita, V. 2004. Towards the computerisation of ANIRCEF Headache Centres. Presentation of AIDA CEFALEE, a computer assisted diagnosis database for the management of headache patients. Neurological Sciences 25, 3, s218–s222.Google Scholar
Dong, Z., Yin, Z., He, M., Chen, X., Lv, X., and Yu, S. 2014. Validation of a guideline-based decision support system for the diagnosis of primary headache disorders based on ICHD-3 beta. The journal of headache and pain 15, 1, 40.Google Scholar
Donovan, J. J. 1976. Database system approach to management descision support. ACM Trans. Database Syst. 1, 4, 344–369.Google Scholar
Eslami, V., Rouhani-Esfahani, S., Hafezi-Nejad, N., Refaeian, F., Abdi, S., and Togha, M. 2013. A computerized expert system for diagnosing primary headache based on International Classification of Headache Disorder (ICHD-II). Springerplus 2, 199, 1–4.Google Scholar
Evans, R. W. 2017. Incidental findings and normal anatomical variants on MRI of the brain in adults for primary headaches. Headache: The Journal of Head and Face Pain 57, 5, 780–791.Google Scholar
International-Headache-Society. 2018. Headache classification committee of the international headache society (IHS) the international classification of headache disorders, 3rd edition. Cephalalgia 38, 1, 1–211.Google Scholar
Michael, M., Moreira, J. E., Shiloach, D., and Wisniewski, R. W. 2007. Scale-up x scale-out: A case study using nutch/lucene. In Proc. of IPDPS’07. 1–8.Google Scholar
Richardson, L. and Ruby, S. 2008. RESTful web services. O’Reilly Media, Inc.Google Scholar
Simić, S., Simić, D., Slankamenac, P., and Simić-Ivkov, M. 2008. Computer-assisted diagnosis of primary headaches. In Proc. of HAIS’08. 314–321.Google Scholar
Stovner, L., Hagen, K., Jensen, R., Katsarava, Z., Lipton, R., Scher, A., Steiner, T., and Zwart, J.-A. 2007. The global burden of headache: A documentation of headache prevalence and disability worldwide. Cephalalgia 27, 3, 193–210.CrossRefGoogle Scholar
Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., and Kroeker, K. I. 2020. An overview of clinical decision support systems: benefits, risks, and strategies for success. npj Digit. Med 3, 1.Google Scholar
Vandewiele, G., De Backere, F., Lannoye, K., Berghe, M. V., Janssens, O., Van Hoecke, S., Keereman, V., Paemeleire, K., Ongenae, F., and De Turck, F. 2018. A decision support system to follow up and diagnose primary headache patients using semantically enriched data. BMC Med Inform Decis Mak 18, 1, 98.Google Scholar