Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28639
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Clinical decision support systems: A visual survey
Author(s): Farooq, Kamran
Khan, Bisma S
Niazi, Muaz A
Leslie, Stephen J
Hussain, Amir
Keywords: cardiovascular decision support systems
CiteSpace
clinical decision support system
scientometrics
visualization
Issue Date: 31-Dec-2018
Citation: Farooq K, Khan BS, Niazi MA, Leslie SJ & Hussain A (2018) Clinical decision support systems: A visual survey. Informatica (Slovenia), 42 (4), pp. 485-505. https://doi.org/10.31449/inf.v42i4.1571.
Abstract: Clinical Decision Support Systems (CDSS) form an important area of research. In spite of its importance, it is difficult for researchers to evaluate the domain primarily because of a considerable spread of relevant literature in interdisciplinary domains. Previous surveys of CDSS have examined the domain from the perspective of individual disciplines. However, to the best of our knowledge, no visual scientometric survey of CDSS has previously been conducted which provides a broader spectrum of the domain from the perspective of multiple disciplines. While traditional systematic literature surveys focus on analyzing literature using arbitrary results, visual surveys allow for the analysis of domains by using complex network-based analytical models. In this paper, we present a detailed visual survey of CDSS literature using important papers selected from highly cited sources on the Clarivate Analytics’ Web of Science. Our key results include the discovery of the articles which have served as key turning points in literature. Additionally, we have identified highly cited authors and the key country of origin of top publications. We also present the universities with the strongest citation bursts. Finally, our network analysis also identifies the key journals and subject categories both in terms of centrality and frequency. It is our belief that this paper will thus serve as an important guide for researchers as well as clinical practitioners interested in identifying key literature and resources in the domain of clinical decision support systems.
DOI Link: 10.31449/inf.v42i4.1571
Rights: This work is licensed under a Creative Commons Attribution 3.0 License (https://creativecommons.org/licenses/by/3.0/).

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