CPC G06T 7/0014 (2013.01) [G06T 11/60 (2013.01); G06V 10/12 (2022.01); G06V 10/25 (2022.01); G06V 10/7715 (2022.01); G16H 10/40 (2018.01); G16H 15/00 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 80/00 (2018.01); G06T 2207/10004 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30024 (2013.01); G06V 2201/03 (2022.01)] | 20 Claims |
1. A computer-implemented method of using at least one machine learning model to categorize a sample in digital pathology, comprising:
receiving one or more cases, each associated with digital images of a pathology specimen, at a digital storage device;
identifying, using the machine learning model, a case of the one or more cases as ready to view;
receiving a selection of the case, the case comprising a plurality of parts;
determining, using the machine learning model, a plurality of features based on the digital images associated with the case;
automatically aggregating, using the machine learning model, a plurality of portions of the pathology specimen into a part index;
determining a diagnosis based on the determined plurality of features, the diagnosis including the part index;
determining, using the machine learning model, a plurality of partial reports using the plurality of features; and
aggregating, the plurality of partial reports into a report, the report including the diagnosis.
|