Analysis of a C. elegans lifespan prediction method based on a bimodal neural network and uncertainty estimation.

ABSTRACT: In recent decades, assays with the nematode Caenorhabditis elegans (C. elegans) have enabled great advances to be made in research on aging. However, performing these assays manually is a laborious task. To solve this problem, numerous C. elegans assay automation techniques are being developed to increase throughput and accuracy. In this paper, a method for predicting the lifespan of C. elegans nematodes using a bimodal neural network is proposed and analyzed. Specifically, the model uses the sequence of images and the count of live C. elegans up to the current day to predict the lifespan curve termination. This network has been trained using a simulator to avoid the labeling costs of training such a model. In addition, a method for estimating the uncerta

SUBMITTER: Garcia-Garvi A 

PROVIDER: S-EPMC9826930 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature