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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Scott JofInnoHlthInfo2018 25-2.png|240px]]</div>
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'''"[[Journal:Learning health systems need to bridge the "two cultures" of clinical informatics and data science|Learning health systems need to bridge the "two cultures" of clinical informatics and data science]]"'''
'''"[[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]]"'''


United Kingdom (U.K.) health research policy and plans for population health management are predicated upon transformative knowledge discovery from operational "big data." Learning health systems require not only data but also feedback loops of knowledge into changed practice. This depends on [[Information management|knowledge management]] and application, which in turn depends upon effective system design and implementation. [[Health informatics|Biomedical informatics]] is the interdisciplinary field at the intersection of health science, social science, and information science and technology that spans this entire scope.
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 />


In the U.K., the separate worlds of health data science ([[bioinformatics]], big data) and effective healthcare system design and implementation ([[Health informatics#Clinical informatics|clinical informatics]], "digital health") have operated as "two cultures." Much National Health Service and social care data is of very poor quality. Substantial research funding is wasted on data cleansing or by producing very weak evidence. There is not yet a sufficiently powerful professional community or evidence base of best practice to influence the practitioner community or the digital health industry. ('''[[Journal:Learning health systems need to bridge the "two cultures" of clinical informatics and data science|Full article...]]''')<br />
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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...)

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