Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
Fuzzy regression analysis: systematic review and bibliography
Statistical regression analysis is a powerful and reliable method to determine the impact of
one or several independent variable (s) on a dependent variable. It is the most widely used …
one or several independent variable (s) on a dependent variable. It is the most widely used …
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
Medical images encryption based on adaptive-robust multi-mode synchronization of chen hyper-chaotic systems
In this paper, a novel medical image encryption method based on multi-mode
synchronization of hyper-chaotic systems is presented. The synchronization of hyper-chaotic …
synchronization of hyper-chaotic systems is presented. The synchronization of hyper-chaotic …
A review on type-2 fuzzy neural networks for system identification
In many engineering problems, the systems dynamics are uncertain, and then, the accurate
dynamic modeling is required. Type-2 fuzzy neural networks (T2F-NNs) are extensively …
dynamic modeling is required. Type-2 fuzzy neural networks (T2F-NNs) are extensively …
[HTML][HTML] An intelligent garment for long COVID-19 real-time monitoring
As monitoring and diagnostic tools for long COVID-19 cases, wearable systems and
supervised learning-based medical image analysis have proven to be useful. Current …
supervised learning-based medical image analysis have proven to be useful. Current …
Prediction of retinopathy in diabetic patients using type-2 fuzzy regression model
NS Bajestani, AV Kamyad, EN Esfahani… - European Journal of …, 2018 - Elsevier
Due to the small sample size of data available in medical research and the levels of
uncertainty and ambiguity associated with medical data, some researchers have employed …
uncertainty and ambiguity associated with medical data, some researchers have employed …
Using the interval Type-2 fuzzy inference systems to compare the impact of speed and space perception on the occurrence of road traffic accidents
A constantly increasing number of deaths on roads forces analysts to search for models that
predict the driver's propensity for road traffic accidents (RTAs). This paper aims to examine a …
predict the driver's propensity for road traffic accidents (RTAs). This paper aims to examine a …
A Novel Interval Type-2 Fuzzy System Identification Method Based on the Modified Fuzzy C-Regression Model
SH Tsai, YW Chen - IEEE Transactions on Cybernetics, 2021 - ieeexplore.ieee.org
In this article, a novel interval type-2 Takagi–Sugeno fuzzy-regression modeling method with
a modified distance definition is proposed. The modified distance definition is developed to …
a modified distance definition is proposed. The modified distance definition is developed to …
Automatic diagnosis of epileptic seizures using entropy-based features and multimodel deep learning approaches
Epilepsy is one of the most common brain diseases, characterised by repeated seizures that
occur on a regular basis. During a seizure, a patient's muscles flex uncontrollably, causing a …
occur on a regular basis. During a seizure, a patient's muscles flex uncontrollably, causing a …