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Hypothyroid Disease Diagnosis with Causal Explanation using Case-based Reasoning and Domain-specific Ontology

Publication Type:

Conference/Workshop Paper

Venue:

Workshop on CBR in the Health Science


Abstract

Explainability of intelligent systems in health-care domain is still in its initial state. Recently, more efforts are made to leverage machine learning in solving causal inference problems of disease diagnosis, prediction and treatments. This research work presents an ontology based causal inference model for hypothyroid disease diagnosis using case-based reasoning. The effectiveness of the proposed method is demonstrated with an example from hypothyroid disease domain. Here, the domain knowledge is mapped into an ontology and causal inference is performed based on this domain-specific ontology. The goal is to incorporate this causal inference model in traditional case-based reasoning cycle enabling explanation for each solved problem. Finally, a mechanism is defined to deduce explanation for a solution to a problem case from the combined causal statements of similar cases. The initial result shows that case-based reasoning can retrieve relevant cases with 95% accuracy.

Bibtex

@inproceedings{Islam5575,
author = {Mir Riyanul Islam and Shaibal Barua and Shahina Begum and Mobyen Uddin Ahmed},
title = {Hypothyroid Disease Diagnosis with Causal Explanation using Case-based Reasoning and Domain-specific Ontology},
month = {September},
year = {2019},
booktitle = {Workshop on CBR in the Health Science},
url = {http://www.es.mdh.se/publications/5575-}
}