Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches

Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches

Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the production of iPSCs and iPSC-derived cell lineages gener...

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Bibliographic Details
Main Authors: Chung-Yueh Lien, Tseng-Tse Chen, En-Tung Tsai, Yu-Jer Hsiao, Ni Lee, Chong-En Gao, Yi-Ping Yang, Shih-Jen Chen, Aliaksandr A. Yarmishyn, De-Kuang Hwang, Shih-Jie Chou, Woei-Chyn Chu, Shih-Hwa Chiou, Yueh Chien
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Cells
Subjects:
induced pluripotent stem cells
retinal pigment epithelial cells
artificial intelligence
deep learning
convolutional neural network
traditional machine learning
Online Access:https://www.mdpi.com/2073-4409/12/2/211

Internet

https://www.mdpi.com/2073-4409/12/2/211

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