A stepwise protocol for neural network modeling of persistent postoperative facial pain in chronic rhinosinusitis
-
Joanna Szaleniec
,
Maciej Szaleniec
und
Paweł Stręk
Abstract
In the artificial neural network field, no universal algorithm of modeling ensures obtaining the best possible model for a given task. Researchers frequently regard artificial neural networks with suspicion caused by the lack of repeatability of single experiments. We propose a systematic approach that may increase the probability of finding the optimal network architecture. In the experiments, the average effectiveness in groups of networks rather than single networks should be compared. Such an approach facilitates the analysis of the results caused by changes in the network parameters, while the influence of chance effects becomes negligible. As an example of this protocol, we present optimization of a neural network applied for prediction of persistent facial pain in patients operated for chronic rhinosinusitis. In the stepwise approach, the percentage of correct predictions was gradually increased from 54% to 75% for the external validation set.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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©2016 by De Gruyter
Artikel in diesem Heft
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- Influence of neural network structure and data-set size on its performance in the prediction of height of growth hormone-treated patients
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- A stepwise protocol for neural network modeling of persistent postoperative facial pain in chronic rhinosinusitis
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Artikel in diesem Heft
- Frontmatter
- Review
- Regeneration of knee joint menisci – methods review
- Original Articles
- Influence of neural network structure and data-set size on its performance in the prediction of height of growth hormone-treated patients
- Empirical wavelet transform-based delineator for arterial blood pressure waveforms
- Independent component analysis of EEG data for EGI system
- Model of dental braces for palatal suture expansion with tension analysis of two titanium alloys: Ti-13Nb-13Zr and Ti-6Al-4V
- A stepwise protocol for neural network modeling of persistent postoperative facial pain in chronic rhinosinusitis
- Short Communication
- Data mining with Random Forests as a methodology for biomedical signal classification
