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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: [email protected])
GELSOMINA CATALANO
Affiliation:
DLVSystem Srl, Rende, Italy (e-mail: [email protected])
BERNARDO CUTERI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected])
MARIA CONCETTA MORELLI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected])
NICOLA LEONE
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected], [email protected])
MARCO MANNA
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected], [email protected])
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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.

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