Predicting stemness of HSCs from dynamic cell behavior using machine learning. I (IMAGE)

The Institute of Medical Science, The University of Tokyo

Predicting stemness of HSCs from dynamic cell behavior using machine learning. I

Caption

In a recent study, researchers from The University of Tokyo demonstrated that the expression of the Hlf gene, a key indicator of stemness, could be inferred from cellular kinetics. Using a deep neural network to predict Hlf levels, they found that the number of input images—the amount of temporal information—greatly boosted the accuracy of the model.

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Dr. Takao Yogo from The University of Tokyo, Japan.

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