Deep learning techniques have been applied to electroencephalogram (EEG) signals, with
promising applications in the field of psychiatry. Schizophrenia is one of the most disabling …

Background and objectives The traditional pain measures are qualitative and inaccurate.
Therefore, electroencephalography (EEG) signals have been recently used and analyzed to …

Lateralisation is the quality of a neural function specialised towards one hemisphere of the
brain over the other for a specific activity. Autism individuals possess reduced language …

This research paper stages a deep convolutional neural network-based approach for the
detection of a complex and debilitating mental disorder, schizophrenia. This mental disorder …

Background: The precise differentiation of schizophrenic patients with positive and negative
symptoms is still challenging; hence, psychiatrists mainly focus on diagnosing schizophrenic …

In DR detection, there are a lot of challenges to be faced in order to provide better
performance and accuracy. The problem that still remains in DR detection is selection of …

Background: Psychiatrists diagnose schizophrenia based on clinical symptoms such as
disordered thinking, delusions, hallucinations, and severe distortion of daily functions …

Among variety of meta-heuristic population-based search algorithms, particle swarm
optimization (PSO) with adaptive inertia weight (AIW) has been considered as a versatile …

Şizofreninin (SZ) erken tanısı hastaların daha etkili tedavi görmelerine olanak sağlayarak,
yaşam kalitelerini artırır. Ancak, hastalığın karmaşık ve heterojen bulguları erken klinik …

Plenty of Bayesian-consistent, heuristic and statistical classifiers have been introduced.
Although support vector machines, deep neural networks, and random forests exhibit …