Authors:
Zhengru Shen
and
Marco Spruit
Affiliation:
Department of Information and Computing Sciences, Utrecht University, Princetonplein 5, Utrecht and The Netherlands
Keyword(s):
Open-source Clinical Software, Github Repository, Literature, Web Application.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Society, e-Business and e-Government
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
Nowadays, the effective utilization of open-source software could significantly boost both clinical research and practices, especially in resource-poor countries. However, the plethora of open-source clinical software has left many people unable to quickly locate the appropriate one for their needs. Commonly available software quality metrics and software documentation, such as downloads, forks, stars, and readme files, are useful selection criteria, but they only indicate the software quality from the perspective of IT experts. This paper proposes a method that offers additional insights on the performance and effectiveness of clinical software. It links open-source clinical software with relevant scientific literature, such as papers that use case studies of clinical software to reveal the strength and weakness of a given software from the clinical perspective. To interactively present the open-source clinical software and their related literature, we have developed the LOCATE web
application that enables users to explore related literature for a given open-source clinical software. Moreover, the peer-review cycle of the application allows users to improve the application by confirming, adding or removing related literature. An evaluation experiment of the five most popular open-source clinical tools demonstrates the potential usefulness of LOCATE.
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