Schizophrenia

Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study.

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) pat...

Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.

BACKGROUND: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physi...

Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI.

Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI ...

A novel fuzzy rough selection of non-linearly extracted features for schizophrenia diagnosis using fMRI.

BACKGROUND AND OBJECTIVES: Schizophrenia is a severe brain disorder primarily diagnosed through exte...

Does this robot have a mind? Schizophrenia patients' mind perception toward humanoid robots.

A Deep-Dream Virtual Reality Platform for Studying Altered Perceptual Phenomenology.

Altered states of consciousness, such as psychotic or pharmacologically-induced hallucinations, prov...

Working Memory and Decision-Making in a Frontoparietal Circuit Model.

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distrib...

Influence of facial feedback during a cooperative human-robot task in schizophrenia.

Rapid progress in the area of humanoid robots offers tremendous possibilities for investigating and ...

Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features.

Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive ...

Improving individual predictions: Machine learning approaches for detecting and attacking heterogeneity in schizophrenia (and other psychiatric diseases).

Psychiatric diseases are very heterogeneous both in clinical manifestation and etiology. With the re...

Individualized prediction of psychosis in subjects with an at-risk mental state.

Early intervention strategies in psychosis would significantly benefit from the identification of re...

A state-independent network of depressive, negative and positive symptoms in male patients with schizophrenia spectrum disorders.

Depressive symptoms occur frequently in patients with schizophrenia. Several factor analytical studi...

A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals.

BACKGROUND: Linguistic analysis of publicly available Twitter feeds have achieved success in differe...

Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis.

OBJECTIVE: Structural and functional abnormalities have been reported in the brain of patients with ...

BrainAGE score indicates accelerated brain aging in schizophrenia, but not bipolar disorder.

BrainAGE (brain age gap estimation) is a novel morphometric parameter providing a univariate score d...

Auditory prediction errors as individual biomarkers of schizophrenia.

Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence co...

Using short-range and long-range functional connectivity to identify schizophrenia with a family-based case-control design.

Abnormal short-range and long-range functional connectivities (FCs) have been implicated in the neur...

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis.

A relatively large number of studies have investigated the power of structural magnetic resonance im...

Multi-center machine learning in imaging psychiatry: A meta-model approach.

One of the biggest problems in automated diagnosis of psychiatric disorders from medical images is t...

Mimicking Neurotransmitter Release in Chemical Synapses via Hysteresis Engineering in MoS Transistors.

Neurotransmitter release in chemical synapses is fundamental to diverse brain functions such as moto...

Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.

OBJECTIVE: Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at ...