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An Architecture for Ontology-based Semantic Reasoning Using LLMs in Healthcare Domain

Authors:
Muge Olucoglu
Okan Bursa

Keywords: semantic reasoning; ontology; healthcare; knowledge graph; large language model.

Abstract:
This study presents research research that involves examining various methods used in the field of health services and proposing a new architecture for more precise diagnosis from health records. Traditional and modern methods such as Electronic Health Records (EHR), Clinical Decision Support Systems (CDSS), Natural Language Processing (NLP)-based analytics, and Machine Learning (ML) techniques are discussed, highlighting their advantages, disadvantages, and usage areas. Based on these evaluations, a new method involving ontologies and Large Language Models (LLMs) has been developed to provide a more effective solution for healthcare informatics. The proposed approach is a candidate solution to achieve higher accuracy, speed, and flexibility by integrating ontologies, LLM and reasoners.

Pages: 8 to 13

Copyright: Copyright (c) IARIA, 2024

Publication date: September 29, 2024

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-68558-190-9

Location: Venice, Italy

Dates: from September 29, 2024 to October 3, 2024