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What is Clinical Decision Support System (CDSS)

Chapter 1
Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems
An information technology that enhances medical-related decisions.
Published in Chapter:
Integrating Knowledge-Driven and Data-Driven Methodologies for an Efficient Clinical Decision Support System
Okure Udo Obot (Department of Computer Science, University of Uyo, Nigeria), Kingsley Friday Attai (Ritman University, Ikot Ekpene, Nigeria), and Gregory O. Onwodi (National Open University of Nigeria, Nigeria)
Copyright: © 2023 |Pages: 28
DOI: 10.4018/978-1-6684-5092-5.ch001
Abstract
Clinical decision support systems (CDSSs) symbolize a significant transformation in healthcare delivery. CDSS enhances healthcare delivery by enabling personnel in medical institutions to handle complex decision-making processes with great speed and high accuracy. Decision support systems are developed using a knowledge-driven or data-driven approach, although both approaches seem to complement each other. For instance, while data-driven is an objective approach, the knowledge-driven approach is subjective. The objective of the chapter is to elaborate on the integration of data-driven and knowledge-driven methodologies for clinical decision support systems. An overview of data-driven and knowledge-driven approaches is presented with a review of both current and dated literature on the subject with numerous viewpoints to support the discussion. Based on the findings, a promising methodology is proposed that integrates data-driven and knowledge-driven approaches and is believed to overcome the challenges of the individual approaches.
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Chapter 9
Conceptual Design Principles for Data-Driven Clinical Decision Support Systems (CDSS): Developing Useful and Relevant CDSS
Software which provides clinicians with knowledge and patient-specific information, intelligently filtered, or presented at appropriate times, to enhance decision-making in the clinical workflow.
Published in Chapter: Conceptual Design Principles for Data-Driven Clinical Decision Support Systems (CDSS): Developing Useful and Relevant CDSS; From: Health Informatics and Patient Safety in Times of Crisis
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Chapter 24
mHealth Environments for Chronic Disease Management
An interactive intelligent system developed with computer software, which is designed to assist physicians and other health professionals in decision making tasks, such as determining diagnosis of patient data or categorizing patients based on their health condition.
Published in Chapter: mHealth Environments for Chronic Disease Management; From: Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions
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Chapter 30
Supporting an Interdisciplinary Healthcare Team with a Multi-Agent System
Any computer system that helps healthcare practitioners make clinical decisions.
Published in Chapter: Supporting an Interdisciplinary Healthcare Team with a Multi-Agent System; From: Encyclopedia of E-Health and Telemedicine
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Chapter 6
Machine Learning Approaches to Automated Medical Decision Support Systems
Systems to assist patients and health care professionals on healthcare processes, such as triage, early detection of diseases, identification of changes in health symptoms, patients' self-reporting, evaluation of treatment, and monitoring.
Published in Chapter: Machine Learning Approaches to Automated Medical Decision Support Systems; From: Handbook of Research on Artificial Intelligence Techniques and Algorithms
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Chapter 8
Systematic Literature Review: XAI and Clinical Decision Support
A technology and a system architecture that uses medical knowledge with clinical data to provide customised advice for an individual patient's care.
Published in Chapter: Systematic Literature Review: XAI and Clinical Decision Support; From: Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems
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Chapter 6
The Development and Impact of China's Digital Transformation in the Medical Industry
A clinical assistant decision-making system that follows evidence-based medicine by learning from a large number of clinical guidelines, pharmacopoeia and high-quality medical records of tertiary hospitals, based on natural language processing, knowledge graph and other AI technologies.
Published in Chapter: The Development and Impact of China's Digital Transformation in the Medical Industry; From: Impact of Digital Transformation on the Development of New Business Models and Consumer Experience
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