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Performance comparison of machine learning techniques in sleep scoring based on wavelet features and neighboring component analysis

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138 days ago
Performance comparison of machine learning techniques in sleep scoring based on wavelet ... https://t.co/5ftlHLZONn #ai #ml #dl
139 days ago
Performance comparison of machine learning techniques in sleep scoring based on wavelet features and neighboring component analysis https://t.co/DwirvE5aNg
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Additional Information

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Behrouz Alizadeh Savareh conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Azadeh Bashiri performed the experiments, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Ali Behmanesh contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Gholam Hossein Meftahi contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

Boshra Hatef conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

Data Deposition

The following information was supplied regarding data availability:

The raw data used in this study is publicly available on the Physionet website:

https://physionet.org/physiobank/database/sleep-edf/

Matlab code for the implementation of the methods are available as Supplemental Files.

Funding

The authors received no funding for this work.


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