Data heterogeneity mitigation in healthcare robotic systems leveraging the Nelder–Mead method
Pritam Khan, Priyesh Ranjan and Sudhir Kumar, Department of Electrical Engineering, Indian Institute of Technology Patna, India
Abstract
Heterogeneity in healthcare data is a cause of concern for the medical professionals. With the increased application of robots in the medical field, data heterogeneity requires to be ad- dressed for improved classification accuracy. In this work, we leverage the Nelder–Mead (NM) optimization method for mitigating data heterogeneity. The NM method is applied on the raw healthcare data to acquire the heterogeneity mitigated data. We classify the electrocardiogram signals from two heterogeneous datasets as ...
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