The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 16, 2024

Filed:

Oct. 04, 2019
Applicant:

Decision Tree, Llc, Greeley, CO (US);

Inventor:

Brandon Lee Goodchild Drake, Greeley, CO (US);

Assignees:

Decision Tree, LLC, Greeley, CO (US);

Veracio Ltd., Salt Lake City, UT (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01N 23/223 (2006.01); G06N 20/00 (2019.01); G01N 23/207 (2018.01); G06F 18/24 (2023.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G01N 23/223 (2013.01); G01N 23/2076 (2013.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06N 20/00 (2019.01);
Abstract

Systems and methods for interpreting high-energy interactions on a sample are described in this application. In particular, this application describes an analysis method that comprises impinging radiation from a source on an analyte, detecting the energy interactions resulting from the impinging radiation using a radiation detector, adjusting the signal from the radiation detector using a machine learning module to emphasize specific parts of the detector signal, training the machine learning module in a supervised or unsupervised manner, producing quantitative and qualitative models using the machine leaning module, and then applying the machine learning module to additional energy interactions. The signal received by the detector can be preprocessed to emphasize specific parts of the detector signal, which is then mapped to a machine learning module for training in a supervised or unsupervised manner. The quantitative and qualitative models derived from this training can be applied to new detector inputs from the same or similar instruments. Other embodiments are described.


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