Modeling adult skeletal stem cell response to laser-machined topographies through deep learning

@article{Mackay2020ModelingAS,
  title={Modeling adult skeletal stem cell response to laser-machined topographies through deep learning},
  author={Benita Scout Mackay and M. Praeger and J. Grant-Jacob and J. Kanczler and R. Eason and R. O. Oreffo and B. Mills},
  journal={Tissue & cell},
  year={2020},
  volume={67},
  pages={
          101442
        }
}
  • Benita Scout Mackay, M. Praeger, +4 authors B. Mills
  • Published 2020
  • Biology, Computer Science, Medicine, Engineering
  • Tissue & cell
  • The response of adult human bone marrow stromal stem cells to surface topographies generated through femtosecond laser machining can be predicted by a deep neural network. The network is capable of predicting cell response to a statistically significant level, including positioning predictions with a probability P < 0.001, and therefore can be used as a model to determine the minimum line separation required for cell alignment, with implications for tissue structure development and tissue… CONTINUE READING

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