Difference between revisions of "Template:Article of the week"

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(Updated article of the week text)
(Updated article of the week text)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Jofre ApplSci2021 11-15.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Demelo Information21 12-8.png|240px]]</div>
'''"[[Journal:Cybersecurity and privacy risk assessment of point-of-care systems in healthcare: A use case approach|Cybersecurity and privacy risk assessment of point-of-care systems in healthcare: A use case approach]]"'''
'''"[[Journal:Design of generalized search interfaces for health informatics|Design of generalized search interfaces for health informatics]]"'''


[[Point-of-care testing|Point-of-care]] (POC) systems are generally used in healthcare to respond rapidly and prevent critical health conditions. Hence, POC systems often handle personal [[Health informatics|health information]], and, consequently, their [[cybersecurity]] and [[Information privacy|privacy]] requirements are of crucial importance. However, assessing these requirements is a significant task. In this work, we propose a use-case approach to assess specifications of cybersecurity and privacy requirements of POC systems in a structured and self-contained form. Such an approach is appropriate since use cases are one of the most common means adopted by developers to derive requirements. As a result, we detail a use case approach in the framework of a real-based healthcare IT infrastructure that includes a [[Health information technology|health information system]], [[Message broker|integration engines]], application servers, web services, [[medical device]]s, smartphone apps, and medical modalities (all data simulated) together with the interaction with participants. Since our use case also sustains the analysis of cybersecurity and privacy risks in different threat scenarios, it also supports decision making and the analysis of compliance considerations. ('''[[Journal:Cybersecurity and privacy risk assessment of point-of-care systems in healthcare: A use case approach|Full article...]]''')<br />
In this paper, we investigate [[Ontology (information science)|ontology]]-supported interfaces for [[health informatics]] search tasks involving large document sets. We begin by providing background on health informatics, [[machine learning]], and ontologies. We review leading research on health informatics search tasks to help formulate high-level design criteria. We then use these criteria to examine traditional design strategies for search interfaces. To demonstrate the utility of the criteria, we apply them to the design of the ONTology-supported Search Interface (ONTSI), a demonstrative, prototype system. ONTSI allows users to plug-and-play document sets and expert-defined domain ontologies through a generalized search interface. ONTSI’s goal is to help align users’ common vocabulary with the domain-specific vocabulary of the plug-and-play document set. We describe the functioning and utility of ONTSI in health informatics search tasks through a [[workflow]] and a scenario. We conclude with a summary of ongoing evaluations, limitations, and future research. ('''[[Journal:Design of generalized search interfaces for health informatics|Full article...]]''')<br />
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''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Cybersecurity and privacy risk assessment of point-of-care systems in healthcare: A use case approach|Cybersecurity and privacy risk assessment of point-of-care systems in healthcare: A use case approach]]
* [[Journal:Fostering reproducibility, reusability, and technology transfer in health informatics|Fostering reproducibility, reusability, and technology transfer in health informatics]]
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}}
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Revision as of 15:33, 30 May 2022

Fig4 Demelo Information21 12-8.png

"Design of generalized search interfaces for health informatics"

In this paper, we investigate ontology-supported interfaces for health informatics search tasks involving large document sets. We begin by providing background on health informatics, machine learning, and ontologies. We review leading research on health informatics search tasks to help formulate high-level design criteria. We then use these criteria to examine traditional design strategies for search interfaces. To demonstrate the utility of the criteria, we apply them to the design of the ONTology-supported Search Interface (ONTSI), a demonstrative, prototype system. ONTSI allows users to plug-and-play document sets and expert-defined domain ontologies through a generalized search interface. ONTSI’s goal is to help align users’ common vocabulary with the domain-specific vocabulary of the plug-and-play document set. We describe the functioning and utility of ONTSI in health informatics search tasks through a workflow and a scenario. We conclude with a summary of ongoing evaluations, limitations, and future research. (Full article...)

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