ArticlePloS one2018
Evolutionary Wavelet Neural Network ensembles for breast cancer and Parkinson's disease prediction.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning for the Diagnosis of Parkinson's Disease: A Review of Literature.Frontiers in aging neuroscience · 2021Pooled it
- Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson's Disease Using Vocal Characteristics: A Comparative Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Predicting Pregnant Women's Abortion: Artificial Neural Network, Wavelet Neural Network and Adaptive Neural Fuzzy Inference System.Advanced biomedical research · 2025Article
- Article
- Parkinson's disease detection based on features refinement through L1 regularized SVM and deep neural network.Scientific reports · 2024Article
- Automatic and Early Detection of Parkinson's Disease by Analyzing Acoustic Signals Using Classification Algorithms Based on Recursive Feature Elimination Method.Diagnostics (Basel, Switzerland) · 2023Article
- English Speech Recognition System Model Based on Computer-Aided Function and Neural Network Algorithm.Computational intelligence and neuroscience · 2022Article
- Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson's disease.Neural computing & applications · 2021Article
- Automated Detection of Parkinson's Disease Based on Multiple Types of Sustained Phonations Using Linear Discriminant Analysis and Genetically Optimized Neural Network.IEEE journal of translational engineering in health and medicine · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wavelet Neural Networks are a combination of neural networks and wavelets and have been mostly used in the area of time-series prediction and control. Recently, Evolutionary Wavelet Neural Networks have been employed to develop cancer prediction models. The present study proposes to use ensembles of Evolutionary Wavelet Neural Networks. The search for a high quality ensemble is directed by a fitness function that incorporates the accuracy of the classifiers both independently and as part of the ensemble itself. The ensemble approach is tested on three publicly available biomedical benchmark datasets, one on Breast Cancer and two on Parkinson's disease, using a 10-fold cross-validation strategy. Our experimental results show that, for the first dataset, the performance was similar to previous studies reported in literature. On the second dataset, the Evolutionary Wavelet Neural Network ensembles performed better than all previous methods. The third dataset is relatively new and this study is the first to report benchmark results.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.