Psychiatry

Depression

Latest AI and machine learning research in depression for healthcare professionals.

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Depression recognition according to heart rate variability using Bayesian Networks.

BACKGROUND: Doctors mainly use scale tests and subjective judgment in the clinical diagnosis of depr...

Getting RID of the blues: Formulating a Risk Index for Depression (RID) using structural equation modeling.

OBJECTIVE: While risk factors for depression are increasingly known, there is no widely utilised dep...

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 nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support.

BACKGROUND: Probabilistic assessments of clinical care are essential for quality care. Yet, machine ...

Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media.

With the rise of social media, millions of people are routinely expressing their moods, feelings, an...

Applying deep neural networks to unstructured text notes in electronic medical records for phenotyping youth depression.

BACKGROUND: We report a study of machine learning applied to the phenotyping of psychiatric diagnosi...

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.

BACKGROUND: Social networking services (SNSs) contain abundant information about the feelings, thoug...

A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD).

Major depressive disorder (MDD), a debilitating mental illness, could cause functional disabilities ...

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study.

BACKGROUND: Early identification and intervention are imperative for suicide prevention. However, at...

Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective.

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic bu...

Depressive Symptoms and Their Interactions With Emotions and Personality Traits Over Time: Interaction Networks in a Psychiatric Clinic.

OBJECTIVE: Associations between depression, personality traits, and emotions are complex and recipro...

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 ...

Antidepressant-like effects of Gan-Mai-Dazao-Tang via monoamine regulatory pathways on forced swimming test in rats.

Depression is a highly prevalent and recurrent mental disorder that impacts all aspects of human lif...

Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from m...

Effectiveness of Electroconvulsive Therapy Augmentation on Clozapine-Resistant Schizophrenia.

OBJECTIVE: This retrospective case series study of the effectiveness of electroconvulsive therapy (E...

Cortico-Striatal-Thalamic Loop Circuits of the Salience Network: A Central Pathway in Psychiatric Disease and Treatment.

The salience network (SN) plays a central role in cognitive control by integrating sensory input to ...

Predictive diagnosis of major depression using NMR-based metabolomics and least-squares support vector machine.

BACKGROUND: Major depressive (MD) disorder is a serious psychiatric disorder that can result in suic...

Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis.

Recent studies have reported an association between psychopathology and subsequent clinical and func...

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