Deep Learning: Automating the Future of Stem Cell Bioimage Analysis

I Gusti Ngurah Krishna Priyaka

Abstract

The use of deep learning has been explored in various fields of science. Deep learning utilizes artificial neural networks which contain neurons arranged in layers to analyze data and generate predictions. Several deep learning architectures have been used in image recognition and analysis, including bioimage analysis in stem cell research. Stem cells, with their differentiation potential, are widely used in drug testing, disease modeling, and regenerative treatments. In stem cell research, it is essential to identify and track which cell lineage stem cells have differentiated into. Until recently, this has been done with the use of molecular labeling and manual methods, which are mostly subjective and error-prone. The use of deep learning to identify and classify stem cells offers potential solutions of automation, and cost-effectiveness, in addition to high performance accuracy. This article summarizes how deep learning can be used in identifying stem cells, along with their current limitations.

Keywords

deep learning; stem cell; bioimage analysis.

Cite This Article

Priyaka, I. G. N. K. (2024). Deep Learning: Automating the Future of Stem Cell Bioimage Analysis. International Journal of Scientific Advances (IJSCIA), Volume 5| Issue 6: Nov-Dec 2024, Pages 1416-1421, URL: https://www.ijscia.com/wp-content/uploads/2024/12/Volume5-Issue6-Nov-Dec-No.744-1416-1421.pdf

Volume 5 | Issue 6: Nov – Dec 2024