CDSS Architecture: Oriented on Hierarchical Reinforcement Learning by Automated Planning

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Author(s): Dmytro Dosyn (Lviv Polytechnic National University, Ukraine)
Copyright: 2023
Pages: 26
Source title: Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems
Source Author(s)/Editor(s): Thomas M. Connolly (DS Partnership, UK), Petros Papadopoulos (University of Strathclyde, UK) and Mario Soflano (Glasgow Caledonian University, UK)
DOI: 10.4018/978-1-6684-5092-5.ch003

Keywords: Business & Management / Decision Support Systems / Health Information Systems / Medical Information Science Reference

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Abstract

Patient-oriented data-driven CDSS architecture, based on adaptive ontology, is proposed as a perspective for a future development of intelligent medical decision support systems. A human body (anatomy and physiology) knowledge base should be the basic component of the system with the possibility to permanently automated update the deeply structured data, both general and personal, using the technologies of ontology learning, natural language processing, and automated planning. Already existing information technologies, standards, and protocols allow implementing such an approach in a healthcare domain in a framework of FHIR HL7.org standard.

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CDSS Architecture: Oriented on Hierarchical Reinforcement Learning by Automated Planning

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