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

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:PACS-RIS Services.png|200px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
A [[picture archiving and communication system]] (PACS) is a digital imaging system composed of a set of components that allow for the digital acquisition, archiving, communication, retrieval, processing, distribution, and display of medical images. The PACS may consist of only a few components or be sufficiently complex to handle a hospital or healthcare enterprise environment. Regardless, it must be durable enough for daily use in a clinical environment, integrate to and from several [[Imaging informatics#Diagnostic imaging modalities|medical imaging modalities]], and have sufficient workstations for technicians utilizing those modalities to perform their work inside and outside the radiology department.[1] PACS benefit healthcare providers by digitally managing medical images, eliminating the need to manually file, retrieve, or transport film jackets. This often saves processing time in both the diagnostics and reporting related to the imagery, especially when integrated with speech recognition technology. ('''[[Picture archiving and communication system|Full article...]]''')<br />
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''
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''Recently featured'': [[Cytopathology]], [[Clinical pathology]], [[Anatomical pathology]]
[[Information]] is the cornerstone of [[research]], from experimental data/[[metadata]] and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging [[laboratory information management system]]s (LIMS) to transform this large information load into useful scientific findings. The development of [[mathematical model]]s that can predict the properties of biological systems is the holy grail of [[computational biology]]. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... ('''[[Journal:Ten simple rules for managing laboratory information|Full article...]]''')<br />
 
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Revision as of 18:03, 10 June 2024

Fig2 Berezin PLoSCompBio23 19-12.png

"Ten simple rules for managing laboratory information"

Information is the cornerstone of research, from experimental data/metadata and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems (LIMS) to transform this large information load into useful scientific findings. The development of mathematical models that can predict the properties of biological systems is the holy grail of computational biology. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... (Full article...)

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