Machine learning for high-energy interactions analysis

An analysis method, comprising:

• receiving a signal from a detector that has detected energy interactions from radiation impinging on an analyte;
• adjusting the signal emitted from the detector using a pre-processing method to emphasize specific features of that signal;
• using a machine learning module to interpret specific parts of the adjusted signal;
• producing a quantitative and/or qualitative model using the machine learning module;
• applying a post-processing method to an output from the machine learning module to determine a metric;
• and
• selecting, based on the metric, a pre-processing method, machine learning module, or post-processing method for use in subsequent data processing.

An analysis system, comprising:

• a radiation source;
• a radiation detector;
• and
• a machine learning module configured to:
• receive a signal from the radiation detector that has detected energy interactions from radiation from the radiation source impinging on an analyte;
• adjust the signal to emphasize specific parts of the detector signal;
• interpret specific parts of the adjusted signal;
• and
• produce a quantitative and/or qualitative model;
• and
• a post-processing module configured to:
• determine a metric based on an output from the machine learning module;
• and
• select, based on the metric, a pre-processing method, machine learning module, or post-processing method for use in subsequent data processing.