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:Fig2 Beauchamp InsightsImaging2022 14.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:GA1 Frede Processes23 11-1.png|240px]]</div>
'''"[[Journal:Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology|Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology]]"'''
'''"[[Journal:Data management of microscale reaction calorimeter using a modular open-source IoT platform|Data management of microscale reaction calorimeter using a modular open-source IoT platform]]"'''


Enormous recent progress in [[Medical test|diagnostic testing]] can enable more accurate [[Medical diagnosis|diagnosis]] and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the “silo” of each diagnostic discipline, diagnostic data are fragmented, and the [[electronic health record]] (EHR) does little to synthesize new and existing data into usable [[information]]. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the EHR, are aggregated and contextualized by [[Informatics (academic field)|informatics]] tools to direct clinical action ... ('''[[Journal:Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology|Full article...]]''')<br />
Unifying research data collection methods and capturing data streams in an organized and standardized manner are becoming increasingly important in [[Laboratory|laboratories]] as digital processes and [[Laboratory automation|automation]] progressively shape the laboratory [[workflow]]s. In this context, the [[internet of things]] (IoT) not only offers the opportunity to minimize time-consuming and repetitive tasks by delegating them to machines, but it also supports scientists in curating data. As a contribution to the establishment of IoT tools in academic research laboratories, a microscale reaction [[calorimeter]] is exemplarily connected to a modular open-source IoT-platform. The microscale calorimeter’s process data is streamed to the data platform for storage and [[Data analysis|analysis]]. Advantages of the platform from academia’s point of view are presented ... ('''[[Journal:Data management of microscale reaction calorimeter using a modular open-source IoT platform|Full article...]]''')<br />
''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology|Integrative diagnostics: The time is now—a report from the International Society for Strategic Studies in Radiology]]
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Revision as of 15:14, 14 August 2023

GA1 Frede Processes23 11-1.png

"Data management of microscale reaction calorimeter using a modular open-source IoT platform"

Unifying research data collection methods and capturing data streams in an organized and standardized manner are becoming increasingly important in laboratories as digital processes and automation progressively shape the laboratory workflows. In this context, the internet of things (IoT) not only offers the opportunity to minimize time-consuming and repetitive tasks by delegating them to machines, but it also supports scientists in curating data. As a contribution to the establishment of IoT tools in academic research laboratories, a microscale reaction calorimeter is exemplarily connected to a modular open-source IoT-platform. The microscale calorimeter’s process data is streamed to the data platform for storage and analysis. Advantages of the platform from academia’s point of view are presented ... (Full article...)
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