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:Fig3 Nguyen HealthInfoSciSys2015 3-Suppl1.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Karaattuthazhathu NatJLabMed23 12-2.png|260px]]</div>
'''"[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]"'''
'''"[[Journal:Design, implementation and operation of a multimodality research imaging informatics repository|Design, implementation and operation of a multimodality research imaging informatics repository]]"'''


Biomedical imaging research increasingly involves acquiring, managing and processing large amounts of distributed imaging data. Integrated systems that combine data, meta-data and workflows are crucial for realising the opportunities presented by advances in imaging facilities. This paper describes the design, implementation and operation of a multi-modality research imaging data management system that manages imaging data obtained from biomedical imaging scanners operated at Monash Biomedical Imaging (MBI), Monash University in Melbourne, Australia. In addition to [[DICOM|Digital Imaging and Communications in Medicine]] (DICOM) images, raw data and non-DICOM biomedical data can be archived and distributed by the system. Imaging data are annotated with meta-data according to a study-centric data model and, therefore, scientific users can find, download and process data easily. The research imaging data management system ensures long-term usability, integrity inter-operability and integration of large imaging data. Research users can securely browse and download stored images and data, and upload processed data via subject-oriented [[informatics]] frameworks including the Distributed and Reflective Informatics System (DaRIS), and the Extensible Neuroimaging Archive Toolkit (XNAT). ('''[[Journal:Design, implementation and operation of a multimodality research imaging informatics repository|Full article...]]''')<br />
For the release of precise and accurate reports of [[Medical test|routine tests]], its necessary to follow a proper [[quality management system]] (QMS) in the [[clinical laboratory]]. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the [[laboratory]] testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory [[analyte]] by Six Sigma analysis and to plan and chart out a better, customized [[quality control]] (QC) plan for each analyte, according to its own sigma value ... ('''[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Full article...]]''')<br />
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Latest revision as of 16:52, 29 April 2024

Fig1 Karaattuthazhathu NatJLabMed23 12-2.png

"Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study"

For the release of precise and accurate reports of routine tests, its necessary to follow a proper quality management system (QMS) in the clinical laboratory. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the laboratory testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory analyte by Six Sigma analysis and to plan and chart out a better, customized quality control (QC) plan for each analyte, according to its own sigma value ... (Full article...)
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