V. Divya^1,*, S. Sendil Kumar², V. Gokula Krishnan³, Manoj Kumar⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1869-1886, 2023, DOI:10.32604/csse.2023.029762 - 03 November 2022

Abstract Signal processing based research was adopted with Electroencephalogram (EEG) for predicting the abnormality and cerebral activities. The proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or not. Early detection and intervention are vital for better prognosis. However, the diagnosis of schizophrenia still depends on clinical observation to date. Without reliable biomarkers, schizophrenia is difficult to detect in its early phase and hence we have proposed this idea. In this work, the… More >

Gurparsad Singh Suri¹, Gurleen Kaur¹, Sara Moein^2,*

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 723-735, 2021, DOI:10.32604/iasc.2021.015049 - 01 March 2021

Abstract Schizophrenia (SZ) is a mental heterogeneous psychiatric disorder with unknown cause. Neuroscientists postulate that it is related to brain networks. Recently, scientists applied machine learning (ML) and artificial intelligence for the detection, monitoring, and prognosis of a range of diseases, including SZ, because these techniques show a high performance in discovering an association between disease symptoms and disease. Regions of the brain have significant connections to the symptoms of SZ. ML has the power to detect these associations. ML interests researchers because of its ability to reduce the number of input features when the data More >

YUQING HE¹, LI GUO¹, JUAN DING¹, HAOWEN LV¹, QUANRUI MA¹, CHEN LI¹, YU SHAO¹, QIANG LIU¹, CHUN ZHANG¹, HAO YANG^1,2,*, JUAN LIU^1,*

BIOCELL, Vol.45, No.2, pp. 417-426, 2021, DOI:10.32604/biocell.2021.013842 - 19 February 2021

Abstract Schizophrenia is a common and serious mental illness characterized by severe impairments in thinking, emotions, and behaviors. Usually, the cognitive deficits of schizophrenia are closely associated with abnormal neurogenesis due to the hypofunction of certain neural receptors such as N-methyl-D-aspartate receptors (NMDARs), which mediates neurotransmission. However, little is known about the involvement of NMDAR1 in regulating hippocampal neurogenesis in schizophrenia. In the current study, we present evidence suggesting that NMDAR1 regulates hippocampal neurogenesis as lentivirus-mediated shRNA silencing NMDAR1 gene or blocking with MK-801 results in abnormal neurogenesis consistently found in schizophrenia. The important finding was More >

Lan Yang¹, Shun Qi^2,3,#, Chen Qiao^1,*, Yanmei Kang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 215-237, 2020, DOI:10.32604/cmes.2020.010796 - 18 September 2020

Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both… More >