In order to study the application of machine learning in myoelectric data, the machine learning method has been used for data mining and analysis so as to find correlation characteristics. More than 2,300 myoelectric examination data from Sichuan Provincial Hospital of Traditional Chinese Medicine (TCM) for 10 months has been collected and recorded. By means of setting the inclusion criteria and excluding the irrelevant factors, the facial nerve electromyography and auditory brainstem response test reports that meet the research criteria have been screened out.

Dataset Files

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[1] zechen li, "MNCS.csv", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/5007-5t85. Accessed: Oct. 10, 2024.
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doi = {10.21227/5007-5t85},
url = {http://dx.doi.org/10.21227/5007-5t85},
author = {zechen li },
publisher = {IEEE Dataport},
title = {MNCS.csv},
year = {2019} }
TY - DATA
T1 - MNCS.csv
AU - zechen li
PY - 2019
PB - IEEE Dataport
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zechen li. (2019). MNCS.csv. IEEE Dataport. http://dx.doi.org/10.21227/5007-5t85
zechen li, 2019. MNCS.csv. Available at: http://dx.doi.org/10.21227/5007-5t85.
zechen li. (2019). "MNCS.csv." Web.
1. zechen li. MNCS.csv [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/5007-5t85
zechen li. "MNCS.csv." doi: 10.21227/5007-5t85