Nuclear Magnetic Resonance (NMR) Spectra Prediction
Description
DEA has a mission to protect communities and save lives. Phase and baseline corrections are important processing steps in the analysis of Nuclear Magnetic Resonance (NMR) spectra. Deep learning achieves excellent results in recognition and segmentation tasks, supporting users with spectra processing and interpretation.
Detailed example
Outputs predicted labels for the spectra.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Fast processing and interpretation of nuclear magnetic resonance spectra.
Audit / financial statement impact
Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
Controls / human review
ATO: Not reported; PIA: Not published