AIMC Topic: Psychiatric Status Rating Scales

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Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
OBJECTIVES: This study investigates whether abnormal neural oscillations, which have been shown to precede the onset of frank psychosis, could be used towards the individualised prediction of psychosis in clinical high-risk patients.

Prediction of remission in obsessive compulsive disorder using a novel machine learning strategy.

International journal of methods in psychiatric research
The study objective was to apply machine learning methodologies to identify predictors of remission in a longitudinal sample of 296 adults with a primary diagnosis of obsessive compulsive disorder (OCD). Random Forests is an ensemble machine learning...

Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods.

Computer methods and programs in biomedicine
Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of depression are some of the factors preventing people from getting help ...

Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

Journal of neural transmission (Vienna, Austria : 1996)
While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do not translate into diagnostic value for the individual patient. Machine-learning generates predictiv...

Phenomenological psychopathology meets machine learning: A multicentric retrospective study (Mu.St.A.R.D.) targeting the role of Aberrant Salience assessment in psychosis detection.

Schizophrenia research
BACKGROUND: The Aberrant Salience (AS) model conceptualizes psychosis onset as the altered attribution of salience to neutral stimuli. The Aberrant Salience Inventory (ASI), a psychometric tool, measures this phenomenon. This study utilized a multi-c...

Concise multi-class anxiety disorder risk assessment: A novel advanced machine learning approach.

Journal of anxiety disorders
Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and intervention. However, traditional survey tools such as DASS-42 are time-consuming in responding and scoring. We used a novel advanced machine learning approach...

Question-based computational language approach outperform ratings scale in discriminating between anxiety and depression.

Journal of anxiety disorders
Major Depression (MD) and General Anxiety Disorder (GAD) are the most common mental health disorders, which typically are assessed quantitatively by rating scales such as PHQ-9 and GAD-7. However, recent advances in natural language processing (NLP) ...

[Patient-tailored approach in tertiary care expert centres using individual dynamic network analysis].

Tijdschrift voor psychiatrie
BACKGROUND: Patients with mental health disorders often have difficulty perceiving associations between multiple symptoms, such as inter-relations between somatic and psychological symptoms. This difficulty may be particularly challenging in patients...

Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.

JAMA psychiatry
IMPORTANCE: Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for meas...