Towards Using Rule-Based Multi-agent System for the Early Detection of Adverse Drug Reactions

Ibrahim, Zina M. (King's College London) | Mallah, Robbie (South London and Maudsley NHS Foundation Trust) | Dobson, Richard J. B. (King's College London)

AAAI Conferences 

Adverse Drug Reactions (ADRs) represent troublesome and potentially fatal side effects of medication treatment. To address the burden induced by ADRs, a preventive approach is necessary whereby clinicians are provided with new data-driven decision-support systems to foresee the factors leading to ADRs and plan precautionary activities effectively. We develop a multi-agent system which monitors the factors leading to the onset of ADRs using information found in the patient records in a hospital setting. The system uses a fuzzy rule-based reasoning engine utilising decision rules developed by clinicians. We evaluate the ability of the framework to identify the cause of ADRs from patient records in a case study involving records of metal health patients. Our work is the first preventive agent-based aid tool.

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