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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Eyal-Altman BMCBioinformatics2017 18.gif|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Soto-Perdomo SoftwareX2023 24.jpg|240px]]</div>
'''"[[Journal:PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine|PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine]]"'''
'''"[[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]]"'''


Numerous publications attempt to predict cancer survival outcome from gene expression data using machine-learning methods. A direct comparison of these works is challenging for the following reasons: (1) inconsistent measures used to evaluate the performance of different models, and (2) incomplete specification of critical stages in the process of knowledge discovery. There is a need for a platform that would allow researchers to replicate previous works and to test the impact of changes in the knowledge discovery process on the accuracy of the induced models.
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 />


We developed the PCM-SABRE platform, which supports the entire knowledge discovery process for cancer outcome analysis. PCM-SABRE was developed using [[KNIME]]. By using PCM-SABRE to reproduce the results of previously published works on breast cancer survival, we define a baseline for evaluating future attempts to predict cancer outcome with machine learning. ('''[[PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine|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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