Deep Learning Model for Predicting Airway Organoid Differentiation.

ABSTRACT:

Background

Organoids are self-organized three-dimensional culture systems and have the advantages of both in vitro and in vivo experiments. However, each organoid has a different degree of self-organization, and methods such as immunofluorescence staining are required for confirmation. Therefore, we established a system to select organoids with high tissue-specific similarity using deep learning without relying on staining by acquiring bright-field images in a non-destructive manner.

Methods

We identified four biomarkers in RNA extracted from airway organoids. We also predicted biomarker expression by image-based analysis of organoids by convolution neural network, a deep learning method.

Results

We predicted airway organoid-specific marker expression from bright-fiel

SUBMITTER: Lim MH 

PROVIDER: S-EPMC10645934 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature