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Schizophrenia

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The Contribution of Explainable Machine Learning Algorithms Using ROI-based Brain Surface Morphology Parameters in Distinguishing Early-onset Schizophrenia From Bipolar Disorder.

Academic radiology
RATIONALE AND OBJECTIVES: To differentiate early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) using surface-based morphometry measurements and brain volumes using machine learning (ML) algorithms.

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis.

Translational psychiatry
The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structura...

Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images.

Physical and engineering sciences in medicine
Schizophrenia (SZ) has been acknowledged as a highly intricate mental disorder for a long time. In fact, individuals with SZ experience a blurred line between fantasy and reality, leading to a lack of awareness about their condition, which can pose s...

Diagnosing schizophrenia using deep learning: Novel interpretation approaches and multi-site validation.

Brain research
Schizophrenia is a profound and enduring mental disorder that imposes significant negative impacts on individuals, their families, and society at large. The development of more accurate and objective diagnostic tools for schizophrenia can be expedite...

Enhancing drug discovery in schizophrenia: a deep learning approach for accurate drug-target interaction prediction - DrugSchizoNet.

Computer methods in biomechanics and biomedical engineering
Drug discovery relies on the precise prognosis of drug-target interactions (DTI). Due to their ability to learn from raw data, deep learning (DL) methods have displayed outstanding performance over traditional approaches. However, challenges such as ...

Impaired perception of a partner's synchronizing behavior reduces positive attitude toward humanoid robot in schizophrenia patients.

Schizophrenia research
As interpersonal synchrony plays a key role in building rapport, the perception of another agent's synchronizing behavior could be an important feature to assess, especially with patients with social deficits such as in schizophrenia. Twenty-four sch...

Illusory generalizability of clinical prediction models.

Science (New York, N.Y.)
It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically based on investigators observing a model's success in one or two d...

Identification of Diagnostic Schizophrenia Biomarkers Based on the Assessment of Immune and Systemic Inflammation Parameters Using Machine Learning Modeling.

Sovremennye tekhnologii v meditsine
UNLABELLED: Disorders of systemic immunity and immune processes in the brain have now been shown to play an essential role in the development and progression of schizophrenia. Nevertheless, only a few works were devoted to the study of some immune pa...

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

Journal of affective disorders
BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing trea...

Computerized analysis of facial expression reveals objective indices of blunted facial affect.

European archives of psychiatry and clinical neuroscience
Blunted affect is associated with severe mental illness, particularly schizophrenia. Mechanisms of blunted affect are poorly understood, potentially due to a lack of phenomenological clarity. Here, we examine clinician rated blunted affect and comput...