RAMANMETRIX: a delightful way to analyze Raman spectra
- URL: http://arxiv.org/abs/2201.07586v1
- Date: Wed, 19 Jan 2022 13:20:28 GMT
- Title: RAMANMETRIX: a delightful way to analyze Raman spectra
- Authors: Darina Storozhuk, Oleg Ryabchykov, Juergen Popp, Thomas Bocklitz
- Abstract summary: One of the factors that obstruct the integration of Raman spectroscopic tools into clinical routines is the complexity of the data processing workflow.
Here, RAMANMETRIX is introduced as a user-friendly software with an intuitive web-based graphical user interface (GUI)
The software can be used both for model training and for the application of the pretrained models onto new data sets.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Although Raman spectroscopy is widely used for the investigation of
biomedical samples and has a high potential for use in clinical applications,
it is not common in clinical routines. One of the factors that obstruct the
integration of Raman spectroscopic tools into clinical routines is the
complexity of the data processing workflow. Software tools that simplify
spectroscopic data handling may facilitate such integration by familiarizing
clinical experts with the advantages of Raman spectroscopy.
Here, RAMANMETRIX is introduced as a user-friendly software with an intuitive
web-based graphical user interface (GUI) that incorporates a complete workflow
for chemometric analysis of Raman spectra, from raw data pretreatment to a
robust validation of machine learning models. The software can be used both for
model training and for the application of the pretrained models onto new data
sets. Users have full control of the parameters during model training, but the
testing data flow is frozen and does not require additional user input.
RAMANMETRIX is available in two versions: as standalone software and web
application. Due to the modern software architecture, the computational backend
part can be executed separately from the GUI and accessed through an
application programming interface (API) for applying a preconstructed model to
the measured data. This opens up possibilities for using the software as a data
processing backend for the measurement devices in real-time.
The models preconstructed by more experienced users can be exported and
reused for easy one-click data preprocessing and prediction, which requires
minimal interaction between the user and the software. The results of such
prediction and graphical outputs of the different data processing steps can be
exported and saved.
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