公开(公告)号：WO2023288323A2

公开(公告)日：2023-01-19

申请号：PCT/US2022/073806

申请日：2022-07-15

Applicant: TECHCYTE, INC. ,  NANOSPOT.AL, INC.

Inventor： CAHOON, Benjamin ,  SMITH, Richard ,  SWENSON, Shane ,  WORTHEN, Bryan ,  ZIMMERMAN, Russ ,  REDECKE, Vanessa ,  HAECKER, Hans ,  ASTILL, Mark ,  WENDLING, Rian

IPC: G01N33/86 ,  G01N33/49 ,  G01N33/569 ,  G01N33/68 ,  G16B40/20 ,  G16H30/00 ,  G01N2021/0125 ,  G01N2021/0143 ,  G01N2021/0181 ,  G01N2021/825 ,  G01N21/82 ,  G01N2333/08 ,  G01N2333/165 ,  G01N33/48771 ,  G01N33/4905 ,  G01N33/5304 ,  G01N33/54306 ,  G01N33/54387 ,  G01N33/56983 ,  G01N33/80 ,  G06F18/24 ,  G06T2207/20081 ,  G06T2207/30024 ,  G06T7/0012 ,  G06T7/0014 ,  G06V10/774 ,  G06V20/698 ,  G16H10/40 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40 ,  G16H40/40 ,  G16H40/67 ,  G16H50/20 ,  G16H50/70 ,  G16H80/00

Abstract: Machine learning image analysis for quantitative and qualitative analysis of agglutination samples. A method includes receiving an image of an agglutination assay comprising a negative control sample, a positive control sample, and a test sample. The method includes providing the image to a machine learning algorithm trained to classify agglutination of the test sample on a quantitative scale. The machine learning algorithm calibrates the quantitative scale based at least in part on the negative control sample and the positive control sample.