SPWVD-CNN for automated detection of schizophrenia patients using EEG signals
Schizophrenia (SZ) is a psychiatric disorder characterized by cognitive dysfunctions,
hallucinations, and delusions, which may lead to lifetime disability. Detection and diagnosis …
hallucinations, and delusions, which may lead to lifetime disability. Detection and diagnosis …
SchizoGoogLeNet: The GoogLeNet‐Based Deep Feature Extraction Design for Automatic Detection of Schizophrenia
Schizophrenia (SZ) is a severe and prolonged disorder of the human brain where people
interpret reality in an abnormal way. Traditional methods of SZ detection are based on …
interpret reality in an abnormal way. Traditional methods of SZ detection are based on …
Depression identification using eeg signals via a hybrid of lstm and spiking neural networks
Depression severity can be classified into distinct phases based on the Beck depression
inventory (BDI) test scores, a subjective questionnaire. However, quantitative assessment of …
inventory (BDI) test scores, a subjective questionnaire. However, quantitative assessment of …
Optimal column subset selection for image classification by genetic algorithms
Many problems in operations research can be solved by combinatorial optimization. Fixed-
length subset selection is a family of combinatorial optimization problems that involve …
length subset selection is a family of combinatorial optimization problems that involve …
Behaviour of pseudo-random and chaotic sources of stochasticity in nature-inspired optimization methods
Stochasticity, noisiness, and ergodicity are the key concepts behind many natural processes
and its modeling is an important part of their implementation. There is a handful of soft …
and its modeling is an important part of their implementation. There is a handful of soft …
Genetic algorithm for the column subset selection problem
Genetic Algorithm for the Column Subset Selection Problem Toggle navigation IEEE Computer
Society Digital Library Jobs Tech News Resource Center Press Room Advertising About Us …
Society Digital Library Jobs Tech News Resource Center Press Room Advertising About Us …
Enhancing Adaboost performance in the presence of class-label noise: A comparative study on EEG-based classification of schizophrenic patients and benchmark …
The performance of Adaboost is highly sensitive to noisy and outlier samples. This is
therefore the weights of these samples are exponentially increased in successive rounds. In …
therefore the weights of these samples are exponentially increased in successive rounds. In …
Genetic algorithm for sampling from scale-free data and networks
A variety of real-world data and networks can be described by a heavy-tailed probability
distribution of its values, vertex degrees, or other significant properties, that follows the …
distribution of its values, vertex degrees, or other significant properties, that follows the …
Time-frequency distribution analysis for electroencephalogram signals of patients with schizophrenia and normal participants
Background: Psychiatrists diagnose schizophrenia based on clinical symptoms such as
disordered thinking, delusions, hallucinations, and severe distortion of daily functions …
disordered thinking, delusions, hallucinations, and severe distortion of daily functions …
Diagnosis of Epileptic Seizures in TLE Patients by Improved Cepstrum Analysis
B Tajadini, H Attar, SRS Nejad… - … on Electrical, Energy …, 2023 - ieeexplore.ieee.org
Epilepsy is a common chronic brain disease characterized by recurrent seizures. The most
effective way to detection the arrival of an epileptic seizure is EEG analysis. Various …
effective way to detection the arrival of an epileptic seizure is EEG analysis. Various …