An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …
Evaluation of risk of bias in neuroimaging-based artificial intelligence models for psychiatric diagnosis: a systematic review
Z Chen, X Liu, Q Yang, YJ Wang, K Miao… - JAMA network …, 2023 - jamanetwork.com
Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
[HTML][HTML] Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …
mental disorder is recognized as a significant breakthrough in the field of psychiatry …
Machine learning techniques for the Schizophrenia diagnosis: a comprehensive review and future research directions
Schizophrenia (SCZ) is a brain disorder where different people experience different
symptoms, such as hallucination, delusion, flat-talk, disorganized thinking, etc. In the long …
symptoms, such as hallucination, delusion, flat-talk, disorganized thinking, etc. In the long …
Magnetic resonance texture analysis reveals stagewise nonlinear alterations of the frontal gray matter in patients with early psychosis
Although gray matter (GM) abnormalities are present from the early stages of psychosis,
subtle/miniscule changes may not be detected by conventional volumetry. Texture analysis …
subtle/miniscule changes may not be detected by conventional volumetry. Texture analysis …
[HTML][HTML] Deep learning in neuroimaging data analysis: applications, challenges, and solutions
LK Avberšek, G Repovš - Frontiers in neuroimaging, 2022 - frontiersin.org
Methods for the analysis of neuroimaging data have advanced significantly since the
beginning of neuroscience as a scientific discipline. Today, sophisticated statistical …
beginning of neuroscience as a scientific discipline. Today, sophisticated statistical …
[HTML][HTML] Gray level co-occurrence matrix and extreme learning machine for Alzheimer's disease diagnosis
S Gao - International Journal of Cognitive Computing in …, 2021 - Elsevier
Alzheimer's disease (AD) is a chronic neurodegenerative disease, which is one of the
biggest challenges in geriatrics. The global incidence of Alzheimer's disease has been on …
biggest challenges in geriatrics. The global incidence of Alzheimer's disease has been on …
Automated rest eeg-based diagnosis of depression and schizophrenia using a deep convolutional neural network
Z Wang, J Feng, R Jiang, Y Shi, X Li, R Xue, X Du… - IEEE …, 2022 - ieeexplore.ieee.org
Depression (DP) and schizophrenia (SCZ) are both highly prevalent psychiatric disorders,
and their diagnosis depends on the examination of symptoms and clinical tests, which can …
and their diagnosis depends on the examination of symptoms and clinical tests, which can …
[HTML][HTML] Advances in Using MRI to Estimate the Risk of Future Outcomes in Mental Health-Are We Getting There?
Schizophrenia is a mental disorder among the leading disabling conditions worldwide (1). It
affects approximately 20 million people and increases 2–3 times the probability of dying …
affects approximately 20 million people and increases 2–3 times the probability of dying …
An effective diagnosis of schizophrenia using kernel ridge regression-based optimized RVFL classifier
Schizophrenia (SCZ) is a severe mental and debilitating neuropsychiatric disorder that
disrupts a person's thought processes, emotions, and behavior. Due to misdiagnosis, self …
disrupts a person's thought processes, emotions, and behavior. Due to misdiagnosis, self …