A parallel neural network approach to prediction of Parkinson's Disease
F Åström, R Koker - Expert systems with applications, 2011 - Elsevier
Recently the neural network based diagnosis of medical diseases has taken a great deal of
attention. In this paper a parallel feed-forward neural network structure is used in the …
attention. In this paper a parallel feed-forward neural network structure is used in the …
RUL prediction using a fusion of attention-based convolutional variational autoencoder and ensemble learning classifier
Predicting the remaining useful life (RUL) is a critical step before the decision-making
process and developing maintenance strategies. As a result, it is frequently impacted by …
process and developing maintenance strategies. As a result, it is frequently impacted by …
Uncertainty based under-sampling for learning naive bayes classifiers under imbalanced data sets
In many real world classification tasks, all data classes are not represented equally. This
problem, known also as the curse of class imbalanced in data sets, has a potential impact in …
problem, known also as the curse of class imbalanced in data sets, has a potential impact in …
Ensemble learning with active example selection for imbalanced biomedical data classification
In biomedical data, the imbalanced data problem occurs frequently and causes poor
prediction performance for minority classes. It is because the trained classifiers are mostly …
prediction performance for minority classes. It is because the trained classifiers are mostly …
An active learning based classification strategy for the minority class problem: application to histopathology annotation
Background Supervised classifiers for digital pathology can improve the ability of physicians
to detect and diagnose diseases such as cancer. Generating training data for classifiers is …
to detect and diagnose diseases such as cancer. Generating training data for classifiers is …
Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets
The Coronavirus pandemic caused by the novel SARS-CoV-2 has significantly impacted
human health and the economy, especially in countries struggling with financial resources …
human health and the economy, especially in countries struggling with financial resources …
Automatic classification of flying bird species using computer vision techniques
Bird populations are identified as important biodiversity indicators, so collecting reliable
population data is important to ecologists and scientists. However, existing manual …
population data is important to ecologists and scientists. However, existing manual …
Performance comparison of heterogeneous classifiers for detection of Parkinson's disease using voice disorder (dysphonia)
Speech signal processing and its recognition system have gained a lot of attention from last
few years due to its widespread application. In this study, we have conducted a comparative …
few years due to its widespread application. In this study, we have conducted a comparative …
Sensors on textile substrates for home-based healthcare monitoring
TH Kang, C Merritt, B Karaguzel… - … Diagnosis and Home …, 2006 - ieeexplore.ieee.org
In this paper we describe progress in developing textile-based sensors for wearable
physiological monitoring systems. Active electrodes on nonwoven textile substrates are …
physiological monitoring systems. Active electrodes on nonwoven textile substrates are …
Neural networks to diagnose the Parkinson's disease
M Can - Southeast Europe Journal of Soft Computing, 2013 - inquiry.ius.edu.ba
To identify the presence of Parkinson's disease, a neural network system with back
propagation together with a majority voting scheme is presented in this paper. The data …
propagation together with a majority voting scheme is presented in this paper. The data …