Machine learning for optical chemical multi-analyte imaging: Why we should dare and why it’s not wit...
Machine learning for optical chemical multi-analyte imaging: Why we should dare and why it’s not without risks
About this item
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Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
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Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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Scope and Contents
Contents
Simultaneous sensing of metabolic analytes such as pH and O
2
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 dire...
Alternative Titles
Full title
Machine learning for optical chemical multi-analyte imaging: Why we should dare and why it’s not without risks
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10185573
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10185573
Other Identifiers
ISSN
1618-2642
E-ISSN
1618-2650
DOI
10.1007/s00216-023-04678-8
