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Machine learning approaches for clinical psychology and psychiatry
Machine learning approaches for clinical psychology and psychiatry explicitly focus on
learning statistical functions from multidimensional data sets to make generalizable …
learning statistical functions from multidimensional data sets to make generalizable …
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 …
[HTML][HTML] Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression
M Cai, Y Ji, Q Zhao, H Xue, Z Sun, H Wang, Y Zhang… - Neuroimage, 2024 - Elsevier
It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is
present in patients with schizophrenia, yet there are inconsistencies in the relevant findings …
present in patients with schizophrenia, yet there are inconsistencies in the relevant findings …
Cerebellar volume and cerebellocerebral structural covariance in schizophrenia: a multisite mega-analysis of 983 patients and 1349 healthy controls
Although cerebellar involvement across a wide range of cognitive and neuropsychiatric
phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia …
phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia …
Neuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophrenia
Technical developments and improved access to neuroimaging techniques have brought us
closer to understanding the neuropathological origins of schizophrenia. Using data-driven …
closer to understanding the neuropathological origins of schizophrenia. Using data-driven …
Identifying schizophrenia using structural MRI with a deep learning algorithm
Objective Although distinctive structural abnormalities occur in patients with schizophrenia,
detecting schizophrenia with magnetic resonance imaging (MRI) remains challenging. This …
detecting schizophrenia with magnetic resonance imaging (MRI) remains challenging. This …
Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large‐scale multi‐sample study
Abstract Machine learning is becoming an increasingly popular approach for investigating
spatially distributed and subtle neuroanatomical alterations in brain‐based disorders …
spatially distributed and subtle neuroanatomical alterations in brain‐based disorders …
The function biomedical informatics research network data repository
Abstract The Function Biomedical Informatics Research Network (FBIRN) developed
methods and tools for conducting multi-scanner functional magnetic resonance imaging …
methods and tools for conducting multi-scanner functional magnetic resonance imaging …
Estimating brain age based on a uniform healthy population with deep learning and structural magnetic resonance imaging
Numerous studies have established that estimated brain age constitutes a valuable
biomarker that is predictive of cognitive decline and various neurological diseases. In this …
biomarker that is predictive of cognitive decline and various neurological diseases. In this …
Disrupted local functional connectivity in schizophrenia: an updated and extended meta-analysis
M Cai, R Wang, M Liu, X Du, K Xue, Y Ji, Z Wang… - Schizophrenia, 2022 - nature.com
Neuroimaging studies have shown that schizophrenia is associated with disruption of
resting-state local functional connectivity. However, these findings vary considerably, which …
resting-state local functional connectivity. However, these findings vary considerably, which …