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A Comprehensive Analysis Using Maximum Likelihood Estimation and Artificial Neural Networks for Modeling Arthritic Pain Relief Data

  • Deepthy G S EMAIL logo , Sujesh Areekara and Nicy Sebastian
Published/Copyright: November 14, 2024
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Abstract

The primary motivation behind this study is to precisely predicting the behaviour of the distribution by employing neural networks and enhancing its performance through maximum likelihood estimation. The numerical findings were compared to the predictions derived from the multilayer artificial neural network model developed with seven neurons in the hidden layer. The R value was 0.999 and the deviation values were less than 0.045  for the artificial neural network models. Also, the results of a numerical investigation using maximum likelihood estimation agree exactly with those obtained from predictions made using artificial neural networks. The findings of this study reveal that neural networks might be a very promising tool for clinical data analysis.

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Received: 2024-06-02
Revised: 2024-10-08
Accepted: 2024-10-27
Published Online: 2024-11-14
Published in Print: 2025-05-01

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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