日本薬理学会年会要旨集
Online ISSN : 2435-4953
第92回日本薬理学会年会
セッションID: 92_2-S16-4
会議情報

シンポジウム
機械学習の多能性幹細胞研究への応用
*湯浅 慎介
著者情報
会議録・要旨集 オープンアクセス

詳細
抄録

Deep learning technology is rapidly advancing, and is now used to solve complex problems. induced pluripotent stem cells (iPSCs) can be used for several purposes such as regenerative medicine, disease modeling study and drug screening. It is inevitable to identify iPSC-derived differentiated cells in microscopy for any use. Here, we used deep learning to establish an automated method to identify endothelial cells derived from iPSCs, without the need for immunostaining or lineage tracing.

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