US 12,424,001 B2
Predicting patient responses to a chemical substance
Wenzhi Cao, Seattle, WA (US); Yechi Ma, Lawrenceville, NJ (US); and Qi Tang, Bridgewater, NJ (US)
Assigned to Sanofi, Paris (FR)
Appl. No. 17/633,116
Filed by Sanofi, Paris (FR)
PCT Filed Aug. 10, 2020, PCT No. PCT/US2020/045624
§ 371(c)(1), (2) Date Feb. 4, 2022,
PCT Pub. No. WO2021/030270, PCT Pub. Date Feb. 18, 2021.
Claims priority of provisional application 62/886,199, filed on Aug. 13, 2019.
Claims priority of application No. 20305030 (EP), filed on Jan. 16, 2020.
Prior Publication US 2022/0318993 A1, Oct. 6, 2022
Int. Cl. G06V 20/69 (2022.01); G06T 7/00 (2017.01); G06V 10/44 (2022.01); G06V 10/50 (2022.01); G06V 10/82 (2022.01)
CPC G06V 20/695 (2022.01) [G06T 7/0012 (2013.01); G06V 10/454 (2022.01); G06V 10/50 (2022.01); G06V 10/82 (2022.01); G06V 20/698 (2022.01); G06T 2207/20021 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/03 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A data processing system, comprising:
a computer-readable memory comprising computer-executable instructions; and
at least one processor configured to execute executable logic including an artificial neural network trained to predict a response to a chemical substance by identifying one or more discrete biological tissue components in an input biological image, wherein when the at least one processor is executing the computer-executable instructions, the at least one processor is configured to carry out operations comprising:
receiving image data representing a biological image of a patient;
processing the image data using the artificial neural network and in accordance with trained values of a set of artificial neural network parameters to generate a response score that defines a predicted response of the patient to the chemical substance, wherein the processing comprises, at each of a plurality of time steps in a sequence of time steps:
obtaining current location data for the time step that defines a location of a current patch of the biological image;
processing the current patch of the biological image using a feature extraction module of the artificial neural network to generate a feature representation of the current patch of the biological image that characterizes locations of discrete biological tissue components in the current patch of the biological image;
processing the feature representation of the current patch of the biological image using a location module of the artificial neural network to generate a next location data for a next time step that defines a location of a next patch of the biological image to be processed at a next time step; and
providing the next location data for processing at the next time step in the sequence of time steps; and
wherein the processing further comprises generating the response score that defines the predicted response of the patient to the chemical substance based on the feature representations of the patches of the biological image.