US 12,170,147 B1
Glaucoma detection and early diagnosis by combined machine learning based risk score generation and feature optimization
Alauddin Bhuiyan, Queens Village, NY (US)
Assigned to IHEALTHSCREEN INC., Queens Village, NY (US)
Filed by iHealthScreen Inc., Queens Village, NY (US)
Filed on Mar. 26, 2024, as Appl. No. 18/616,876.
Application 18/616,876 is a continuation in part of application No. 18/219,433, filed on Jul. 7, 2023, granted, now 11,941,809, issued on Mar. 26, 2024.
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 50/20 (2018.01); G06Q 10/1093 (2023.01); G06T 7/00 (2017.01); G06V 10/44 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01); G06V 40/18 (2022.01); G16H 15/00 (2018.01); G16H 50/30 (2018.01)
CPC G16H 50/20 (2018.01) [G06Q 10/1095 (2013.01); G06T 7/0012 (2013.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01); G06V 40/18 (2022.01); G16H 15/00 (2018.01); G16H 50/30 (2018.01); G06V 2201/03 (2022.01)] 19 Claims
OG exemplary drawing
 
1. A method of detecting glaucoma, the method comprising: pre-training at least one neural network model of a plurality of neural network models using a dataset, the pre-training including: generating a plurality of vectors based on eye image variations within the dataset, wherein each vector includes a plurality of labels designating eye conditions; assigning a class label to each vector based on the plurality of labels; and generating a glaucoma-specific pre-trained model based on the assigned class labels; training the plurality of neural network models based on a plurality of indications of glaucoma based on retinal data; simultaneously generating a risk score associated with each of the plurality of indications based on the trained plurality of neural network models; combining the risk score associated with each of the plurality of indications, a socio-demographic parameter, and a presence of diabetes as a feature vector, based on a classification model, generating a probability score of glaucoma based on the feature vector, using the trained plurality of neural network models; producing based on the probability score a likelihood of glaucoma; and determining whether glaucoma is present based on the likelihood of glaucoma.