Detecting cells of interest in large image datasets using artificial intelligence

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United States of America

PATENT NO 11989960
APP PUB NO 20220172496A1
SERIAL NO

17432832

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Abstract

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A method for selecting a final model for detecting cells of interest in image datasets includes dividing a curated image dataset into a training set, a validation set, and a testing set where each image in the curated image dataset has been labeled as positive or negative for a cell of interest. The method trains each model of an ensemble of neural networks using the training and validation sets. Next, each model of the ensemble is tested using the testing set and the predictions of the ensemble are combined. The combined prediction is compared to the label and the method determines whether the combined prediction satisfies a pre-determined level of detection (LOD). If so, the method outputs the ensemble as a final ensemble. If not, the method modifies a hyperparameter of at least one of the models of the ensemble until the combined prediction satisfies the pre-determined LOD.

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Patent Owner(s)

  • BLUEROCK THERAPEUTICS LP

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Burnett, Benjamin Adam New York, US 1 1
Wilkinson,, Jr Dan Charles Fremont, US 3 1

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