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

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(Updated article of the week text)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Mencacci FrontCellInfectMicro2023 13.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Ayaz Healthcare23 11-12.png|240px]]</div>
'''"[[Journal:Laboratory automation, informatics, and artificial intelligence: Current and future perspectives in clinical microbiology|Laboratory automation, informatics, and artificial intelligence: Current and future perspectives in clinical microbiology]]"'''
'''"[[Journal:Transforming healthcare analytics with FHIR: A framework for standardizing and analyzing clinical data|Transforming healthcare analytics with FHIR: A framework for standardizing and analyzing clinical data]]"'''


[[Clinical laboratory|Clinical diagnostic laboratories]] produce one product—[[information]]—and for this to be valuable, the information must be clinically relevant, accurate, and timely. Although diagnostic information can clearly improve patient outcomes and decrease healthcare costs, technological challenges and [[laboratory]] [[workflow]] practices affect the timeliness and clinical value of diagnostics. This article will examine how prioritizing laboratory practices in a patient-oriented approach can be used to optimize technology advances for improved patient care. ... ('''[[Journal:Laboratory automation, informatics, and artificial intelligence: Current and future perspectives in clinical microbiology|Full article...]]''')<br />
In this study, we discuss our contribution to building a [[Data analysis|data analytic]] framework that supports clinical statistics and analysis by leveraging a scalable standards-based data model named [[Fast Healthcare Interoperability Resources]] (FHIR). We developed an intelligent algorithm that is used to facilitate the clinical data analytics process on FHIR-based data. We designed several [[workflow]]s for patient clinical data used in two [[hospital information system]]s (HISs), namely patient registration systems (PRSs) and [[laboratory information system]]s (LIS). These workflows exploit various FHIR [[application programming interface]]s (API) to facilitate patient-centered and cohort-based interactive analyses. We developed a FHIR database implementation that utilizes FHIR APIs and a range of operations to facilitate descriptive data analytics (DDA) and patient cohort selection ... ('''[[Journal:Transforming healthcare analytics with FHIR: A framework for standardizing and analyzing clinical data|Full article...]]''')<br />
''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Laboratory automation, informatics, and artificial intelligence: Current and future perspectives in clinical microbiology|Laboratory automation, informatics, and artificial intelligence: Current and future perspectives in clinical microbiology]]
* [[Journal:Registered data-centered lab management system based on data ownership security architecture|Registered data-centered lab management system based on data ownership security architecture]]
* [[Journal:Registered data-centered lab management system based on data ownership security architecture|Registered data-centered lab management system based on data ownership security architecture]]
* [[Journal:FAIR Health Informatics: A health informatics framework for verifiable and explainable data analysis|FAIR Health Informatics: A health informatics framework for verifiable and explainable data analysis]]
* [[Journal:FAIR Health Informatics: A health informatics framework for verifiable and explainable data analysis|FAIR Health Informatics: A health informatics framework for verifiable and explainable data analysis]]
* [[Journal:Guideline for software life cycle in health informatics|Guideline for software life cycle in health informatics]]
}}
}}

Revision as of 16:12, 20 November 2023

Fig2 Ayaz Healthcare23 11-12.png

"Transforming healthcare analytics with FHIR: A framework for standardizing and analyzing clinical data"

In this study, we discuss our contribution to building a data analytic framework that supports clinical statistics and analysis by leveraging a scalable standards-based data model named Fast Healthcare Interoperability Resources (FHIR). We developed an intelligent algorithm that is used to facilitate the clinical data analytics process on FHIR-based data. We designed several workflows for patient clinical data used in two hospital information systems (HISs), namely patient registration systems (PRSs) and laboratory information systems (LIS). These workflows exploit various FHIR application programming interfaces (API) to facilitate patient-centered and cohort-based interactive analyses. We developed a FHIR database implementation that utilizes FHIR APIs and a range of operations to facilitate descriptive data analytics (DDA) and patient cohort selection ... (Full article...)
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