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Quantifying the Impact of Data Characteristics on the Transferability of Sleep Stage Scoring Models

Code for the model in the paper Quantifying the impact of data characteristics on the transferability of sleep stage scoring models by Akara Supratak and Peter Haddawy from the Faculty of ICT, Mahidol University.

This work has been accepted for publication in Artificial Intelligence in Medicine.

You can also find our accepted version before the publication in arXiv.

Citation

If you find this useful, please cite our work as follows:

@article{supratak2023,
  title = {Quantifying the impact of data characteristics on the transferability of sleep stage scoring models},
  journal = {Artificial Intelligence in Medicine},
  volume = {139},
  pages = {102540},
  year = {2023},
  issn = {0933-3657},
  doi = {https://doi.org/10.1016/j.artmed.2023.102540},
  url = {https://www.sciencedirect.com/science/article/pii/S0933365723000544},
  author = {Akara Supratak and Peter Haddawy},
  keywords = {Sleep stage scoring, Deep learning, Transfer learning},
}

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