US 11,734,819 B2
Deep learning modeling using health screening images
Aly Mohamed, Acton, MA (US); Maria Victoria Sainz de Cea, Somerville, MA (US); and David Richmond, Newton, MA (US)
Filed by Merative US L.P., Ann Arbor, MI (US)
Filed on Jul. 21, 2020, as Appl. No. 16/934,538.
Prior Publication US 2022/0028058 A1, Jan. 27, 2022
Int. Cl. G06T 7/00 (2017.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06F 18/214 (2023.01)
CPC G06T 7/0012 (2013.01) [G06F 18/214 (2023.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30068 (2013.01)] 25 Claims
OG exemplary drawing
 
1. A method for improving health screening using artificial intelligence (AI), comprising:
receiving a user image by an AI system, wherein the AI system includes:
a first AI model trained using labeled training images from prior health screenings to predict a medical condition, wherein the first AI model generates a first set of feature vectors based on the user image;
a second AI model trained using labeled training images from current health screenings to classify images, wherein the second AI model generates a second set of feature vectors based on the user image;
a feature selection algorithm that selects feature vectors from at least one of the first set of feature vectors or the second set of feature vectors to generate selected feature vectors; and
a classification AI model that processes the selected feature vectors to generate a classification output that comprises a prediction score indicative of a likelihood of the medical condition; and
receiving the classification output from the AI system.