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Machine learning for optical chemical multi-analyte imaging

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Bibliographic Details
Main Authors: Silvia E., Zieger, Klaus, Koren
Format: Book
Language:English
Published: Springer 2023
Subjects:
optical chemical multi-analyte imaging
Online Access:https://link.springer.com/article/10.1007/s00216-023-04678-8
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8206
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spelling oai:localhost:PNK-82062023-04-21T04:32:28Z Machine learning for optical chemical multi-analyte imaging Silvia E., Zieger Klaus, Koren optical chemical multi-analyte imaging CC BY Simultaneous sensing of metabolic analytes such as pH and O2 is critical in complex and heterogeneous biological environments where analytes often are interrelated. However, measuring all target analytes at the same time and position is often challenging. A major challenge preventing further progress occurs when sensor signals cannot be directly correlated to analyte concentrations due to additional effects, overshadowing and complicating the actual correlations. In fields related to optical sensing, machine learning has already shown its potential to overcome these challenges by solving nested and multidimensional correlations. Hence, we want to apply machine learning models to fluorescence-based optical chemical sensors to facilitate simultaneous imaging of multiple analytes in 2D. 2023-04-21T04:32:28Z 2023-04-21T04:32:28Z 2023 Book https://link.springer.com/article/10.1007/s00216-023-04678-8 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8206 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic optical chemical multi-analyte imaging
spellingShingle optical chemical multi-analyte imaging
Silvia E., Zieger
Klaus, Koren
Machine learning for optical chemical multi-analyte imaging
description CC BY
format Book
author Silvia E., Zieger
Klaus, Koren
author_facet Silvia E., Zieger
Klaus, Koren
author_sort Silvia E., Zieger
title Machine learning for optical chemical multi-analyte imaging
title_short Machine learning for optical chemical multi-analyte imaging
title_full Machine learning for optical chemical multi-analyte imaging
title_fullStr Machine learning for optical chemical multi-analyte imaging
title_full_unstemmed Machine learning for optical chemical multi-analyte imaging
title_sort machine learning for optical chemical multi-analyte imaging
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s00216-023-04678-8
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8206
_version_ 1763815059539099648
score 8.891145

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