CPC G06V 10/82 (2022.01) [C12M 1/34 (2013.01); G01N 15/14 (2013.01); G01N 15/1404 (2013.01); G01N 15/1429 (2013.01); G01N 15/1434 (2013.01); G01N 15/1459 (2013.01); G01N 15/147 (2013.01); G01N 21/01 (2013.01); G01N 21/27 (2013.01); G01N 21/64 (2013.01); G01N 21/65 (2013.01); G06F 18/2178 (2023.01); G06F 18/28 (2023.01); G06V 10/772 (2022.01); G06V 10/7784 (2022.01); G06V 20/698 (2022.01); G01N 2015/1006 (2013.01); G01N 2015/1413 (2013.01); G01N 2015/1415 (2013.01); G01N 2015/145 (2013.01); G06F 2218/12 (2023.01)] | 18 Claims |
1. A method, comprising:
(a) providing one or more flow cytometers comprising a flow path and a light receiving unit, wherein the light receiving unit comprises one or more sensors;
(b) flowing one or more objects through the flow path of the one or more flow cytometers;
(c) irradiating the one or more objects with a structured illumination pattern as the one or more objects move relative to the structured illumination pattern in a light irradiation region, wherein the light irradiation region is located on at least a portion of the flow path in which the one or more objects flow through;
(d) detecting at least one electromagnetic wave from the one or more objects using the one or more sensors, wherein the one or more objects comprises at least one target object;
(e) converting the least one electromagnetic wave into one or more time-series electrical signals using the light receiving unit; and
(f) analyzing the one or more time-series electrical signals using a machine learning classification model to obtain one or more classification results.
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