CPC G16H 50/20 (2018.01) [G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06T 7/0012 (2013.01); G16H 30/20 (2018.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20104 (2013.01); G06T 2207/30024 (2013.01); G06V 2201/03 (2022.01)] | 20 Claims |
1. A computer-implemented method for identifying a diagnostic feature of a digitized pathology image, the method comprising:
receiving one or more digitized images of a pathology specimen, and medical metadata comprising image metadata, specimen metadata, clinical information, and patient information;
applying a machine learning model to generate one or more predictions based on a presence of one or more pathological conditions in the one or more digitized images;
generating, by the machine learning model, at least one relevant diagnostic feature based on one or more of the image metadata, specimen metadata, or clinical information for output to a display, the at least one relevant diagnostic feature being based on the presence of a region having the one or more pathological conditions beyond a statistical likelihood; and
providing, by the machine learning model, visualization of a foci of interest of the at least one relevant diagnostic features for output to a display, the display including one or more indications of locations of the one or more digitized images being associated with one or more pathological conditions beyond a predetermined value.
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