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

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text)
(Updated article of the week text)
 
(170 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Pratt JforElecHthDataMeth2019 7-1.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Soto-Perdomo SoftwareX2023 24.jpg|240px]]</div>
'''"[[Journal:Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry|Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry]]"'''
'''"[[Journal:OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs|OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs]]"'''
 
OptiGUI DataCollector is a Python 3.8-based graphical user interface (GUI) that facilitates automated data collection in optics and photonics research and development equipment. It provides an intuitive and easy-to-use platform for controlling a wide range of optical instruments, including [[spectrometer]]s and lasers. OptiGUI DataCollector is a flexible and modular framework that enables simple integration with different types of devices. It simplifies experimental workflow and reduces human error by automating parameter control, data acquisition, and [[Data analysis|analysis]]. OptiGUI DataCollector is currently focused on optical mode conversion utilizing fiber optic technologies ... ('''[[Journal:OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs|Full article...]]''')<br />


There is growing interest in the potential for clinical registries that can simultaneously support clinical care, quality improvement (QI), and [[research]]. This multi-purpose model is consistent with the Institute of Medicine’s (IOM’s) vision of a learning health system which “draws research closer to clinical practice by building knowledge development and application into each stage of the health care delivery process.” Gliklich ''et al.'' define a registry as “an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes.” Most pediatric chronic illnesses meet the [[National Institutes of Health]]'s (NIH) definition for rare disease, and as such, multi-center registries are especially important to study and improve care for children with chronic diseases. ('''[[Journal:Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry|Full article...]]''')<br />
<br />
''Recently featured'':
''Recently featured'':
: ▪ [[Journal:Fast detection of 10 cannabinoids by RP-HPLC-UV method in Cannabis sativa L.|Fast detection of 10 cannabinoids by RP-HPLC-UV method in Cannabis sativa L.]]
{{flowlist |
: ▪ [[Journal:What is this sensor and does this app need access to it?|What is this sensor and does this app need access to it?]]
* [[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]
: ▪ [[Journal:AI meets exascale computing: Advancing cancer research with large-scale high-performance computing|AI meets exascale computing: Advancing cancer research with large-scale high-performance computing]]
* [[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]
* [[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]
}}

Latest revision as of 15:05, 17 June 2024

Fig1 Soto-Perdomo SoftwareX2023 24.jpg

"OptiGUI DataCollector: A graphical user interface for automating the data collecting process in optical and photonics labs"

OptiGUI DataCollector is a Python 3.8-based graphical user interface (GUI) that facilitates automated data collection in optics and photonics research and development equipment. It provides an intuitive and easy-to-use platform for controlling a wide range of optical instruments, including spectrometers and lasers. OptiGUI DataCollector is a flexible and modular framework that enables simple integration with different types of devices. It simplifies experimental workflow and reduces human error by automating parameter control, data acquisition, and analysis. OptiGUI DataCollector is currently focused on optical mode conversion utilizing fiber optic technologies ... (Full article...)

Recently featured:

Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=64487"