AIMC Topic: Psychiatric Status Rating Scales

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Machine learning in major depression: From classification to treatment outcome prediction.

CNS neuroscience & therapeutics
AIMS: Major depression disorder (MDD) is the single greatest cause of disability and morbidity, and affects about 10% of the population worldwide. Currently, there are no clinically useful diagnostic biomarkers that are able to confirm a diagnosis of...

Machine-learned selection of psychological questionnaire items relevant to the development of persistent pain after breast cancer surgery.

British journal of anaesthesia
BACKGROUND: Prevention of persistent pain after breast cancer surgery, via early identification of patients at high risk, is a clinical need. Psychological factors are among the most consistently proposed predictive parameters for the development of ...

Semantic measures: Using natural language processing to measure, differentiate, and describe psychological constructs.

Psychological methods
Psychological constructs, such as emotions, thoughts, and attitudes are often measured by asking individuals to reply to questions using closed-ended numerical rating scales. However, when asking people about their state of mind in a natural context ...

Disrupted functional connectivity within the default mode network and salience network in unmedicated bipolar II disorder.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Recent studies demonstrate that functional disruption in resting-state networks contributes to cognitive and affective symptoms of bipolar disorder (BD), however, the functional connectivity (FC) pattern underlying BD II depression within...

Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

Journal of psychiatric research
Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well es...

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

Journal of evaluation in clinical practice
RATIONALE: Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate...

The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning.

Schizophrenia research
Machine learning techniques were used to identify highly informative early psychosis self-report items and to validate an early psychosis screener (EPS) against the Structured Interview for Psychosis-risk Syndromes (SIPS). The Prodromal Questionnaire...