CPC G06F 3/0482 (2013.01) [G06F 3/03543 (2013.01); G06F 3/04883 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06T 7/0012 (2013.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06T 2207/30096 (2013.01)] | 18 Claims |
1. A method comprising the steps of:
a) presenting an image with an overall risk score or classification produced, based on medical image data related to the image, by a machine learning model as to a disease state of a patient represented by the image, wherein the image is augmented with highlighting to indicate two or more regions in the image which were detected by a detection model of the machine learning model and which were, responsive to detection by the detection model, subjected to inference by the machine learning model to generate respective first region-level inferences that were then used to generate the overall risk score or classification produced by the machine learning model;
b) receiving, via a user interface tool, a user input highlighting two or more regions of the image;
c) subjecting the highlighted two or more regions to inference by the machine learning model to generate respective second region-level inferences therefor and generating an updated overall risk score or classification based on the first region-level inferences and the second region-level inferences, wherein generating the updated overall risk score or classification based on the first region-level inferences and the second region-level inferences comprises generating an updated overall risk that is increased by positive values among the second region-level inferences and decreased by increased areas represented by the user-highlighted two or more regions; and
d) presenting the updated overall risk score or classification to the user via a display.
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