Journal ArticleDOI
Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems
TLDR
The proposed semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications has been successfully validated in the case study of type 2 diabetes mellitus inpatient management.About:
This article is published in Computer Methods and Programs in Biomedicine.The article was published on 2016-01-01. It has received 49 citations till now. The article focuses on the topics: Domain knowledge & Knowledge-based systems.read more
Citations
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A Comprehensive Review on Smart Decision Support Systems for Health Care
Mario W. L. Moreira,Joel J. P. C. Rodrigues,Valery V. Korotaev,Jalal Al-Muhtadi,Neeraj Kumar +4 more
TL;DR: A deep review of the state of the art of smart DSSs is presented and the latest developments in intelligent systems to support decision-makers in health care are elaborated on.
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Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis
TL;DR: The literature describing clinical reasoning ontology (CRO)–based clinical decision support systems (CDSSs) is described and the medical knowledge and reasoning concepts and their properties within these ontologies are identified to guide future research.
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Artificial Intelligence Applications in Type 2 Diabetes Mellitus Care: Focus on Machine Learning Methods
Shahabeddin Abhari,Sharareh R. Niakan Kalhori,Mehdi Ebrahimi,Hajar Hasannejadasl,Ali Garavand +4 more
TL;DR: The main applications of AI for type 2 diabetes mellitus care were screening and diagnosis in different stages and support vector machine and naive Bayesian might achieve better performance than other applications due to the type of variables and targets in diabetes-related outcomes classification.
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DDO: a diabetes mellitus diagnosis ontology
Shaker El-Sappagh,Farman Ali +1 more
TL;DR: This study designs an OWL2 diabetes diagnosis ontology (DDO), which can serve as a diabetes knowledge base and supports automatic reasoning and represents a major step toward the development of a new generation of patient-centric decision support tools.
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Mobile Health Technologies for Diabetes Mellitus: Current State and Future Challenges
TL;DR: A critical analysis of challenges that have not been fully met and directions for future research that could improve MH applicability are highlighted.
References
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Standards of medical care in diabetes.
TL;DR: I would like to take issue with the use of the phrase “standards of medical care in diabetes,” which is used to describe diabetes care standards, in the recently updated and circulatedADA 2006 Clinical Practice Recommendations.
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Standards of Medical Care in Diabetes: Response to Power
TL;DR: The title “Standards of Medical Care in Diabetes” was chosen because in the view of the American Diabetes Association (ADA), the recommendations represent what the association considers the “standards” for the care of patients with diabetes.
Ontology Development 101: A Guide to Creating Your First Ontology
TL;DR: An ontology defines a common vocabulary for researchers who need to share information in a domain that includes machine-interpretable definitions of basic concepts in the domain and relations among them.
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The Unified Medical Language System (UMLS): integrating biomedical terminology
TL;DR: The Unified Medical Language System is a repository of biomedical vocabularies developed by the US National Library of Medicine and includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap).
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Knowledge engineering: principles and methods
TL;DR: The paradigm shift from a transfer view to a modeling view is discussed and two approaches which considerably shaped research in Knowledge Engineering are described: Role-limiting Methods and Generic Tasks.