Machine learning for optical chemical multi-analyte imaging
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2023
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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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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 |
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Digital Phenikaa |
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Digital Phenikaa |
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English |
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optical chemical multi-analyte imaging |
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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 |
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1763815059539099648 |
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8.891053 |