ArticleJournal of medical systems2016
A Multilayer Perceptron Based Smart Pathological Brain Detection System by Fractional Fourier Entropy.
Article in Journal of medical systems, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Clinical-level screening of sleep apnea syndrome with single-lead ECG alone is achievable using machine learning with appropriate time windows.Sleep & breathing = Schlaf & Atmung · 2025Article
- Representation Learning Method for Circular Seal Based on Modified MLP-Mixer.Entropy (Basel, Switzerland) · 2023Article
- Deep-Stacked Convolutional Neural Networks for Brain Abnormality Classification Based on MRI Images.Journal of digital imaging · 2023Article
- Sleep Apnea Detection Based on Multi-Scale Residual Network.Life (Basel, Switzerland) · 2022Article
- Artificial neural networks: a practical review of applications involving fractional calculus.The European physical journal. Special topics · 2022Article
- Body fat prediction through feature extraction based on anthropometric and laboratory measurements.PloS one · 2022Article
- Deep Learning-based Classification of Resting-state fMRI Independent-component Analysis.Neuroinformatics · 2021Article
- Quantitative Analysis Methods Using Histogram and Entropy for Detector Performance Evaluation According to the Sensitivity Change of the Automatic Exposure Control in Digital Radiography.Journal of medical systems · 2020Article
- Multi class disorder detection of magnetic resonance brain images using composite features and neural network.Biomedical engineering letters · 2019Article
- Detection of Sleep Apnea from Single-Lead ECG Signal Using a Time Window Artificial Neural Network.BioMed research international · 2019Article
- Feature Selection for Automatic Tuberculosis Screening in Frontal Chest Radiographs.Journal of medical systems · 2018Article
- Multiple Sclerosis Identification Based on Fractional Fourier Entropy and a Modified Jaya Algorithm.Entropy (Basel, Switzerland) · 2018Article
- Nature-Inspired Algorithm for Training Multilayer Perceptron Networks in e-health Environments for High-Risk Pregnancy Care.Journal of medical systems · 2018Article
- Heartbeats Do Not Make Good Pseudo-Random Number Generators: An Analysis of the Randomness of Inter-Pulse Intervals.Entropy (Basel, Switzerland) · 2018Article
- Article
- An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.Journal of medical systems · 2017Article
- Pathological Brain Detection Using Weiner Filtering, 2D-Discrete Wavelet Transform, Probabilistic PCA, and Random Subspace Ensemble Classifier.Computational intelligence and neuroscience · 2017Article
- Wavelet Entropy and Directed Acyclic Graph Support Vector Machine for Detection of Patients with Unilateral Hearing Loss in MRI Scanning.Frontiers in computational neuroscience · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
This work aims at developing a novel pathological brain detection system (PBDS) to assist neuroradiologists to interpret magnetic resonance (MR) brain images. We simplify this problem as recognizing pathological brains from healthy brains. First, 12 fractional Fourier entropy (FRFE) features were extracted from each brain image. Next, we submit those features to a multi-layer perceptron (MLP) classifier. Two improvements were proposed for MLP. One improvement is the pruning technique that determines the optimal hidden neuron number. We compared three pruning techniques: dynamic pruning (DP), Bayesian detection boundaries (BDB), and Kappa coefficient (KC). The other improvement is to use the adaptive real-coded biogeography-based optimization (ARCBBO) to train the biases and weights of MLP. The experiments showed that the proposed FRFE + KC-MLP + ARCBBO achieved an average accuracy of 99.53 % based on 10 repetitions of K-fold cross validation, which was better than 11 recent PBDS methods.
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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.