AIMC Topic: Psychiatric Status Rating Scales
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Using machine learning to develop a five-item short form of the children's depression inventory.
BMC public health
Apr 23, 2024
BACKGROUND: Many adolescents experience depression that often goes undetected and untreated. Identifying children and adolescents at a high risk of depression in a timely manner is an urgent concern. While the Children's Depression Inventory (CDI) is...
Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.
Depression and anxiety
Apr 9, 2024
New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from tele...
Evaluation of the correlation between gaze avoidance and schizophrenia psychopathology with deep learning-based emotional recognition.
Asian journal of psychiatry
Dec 28, 2021
OBJECTIVE: To investigate the correlation between gaze avoidance and psychopathology in patients with schizophrenia through eye movement measurements in real-life interpersonal situations.
Network analysis of trauma in patients with early-stage psychosis.
Scientific reports
Nov 23, 2021
Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are common in psychosis. The present study aimed to perform a network analysis of interactions between ...
Deep graph neural network-based prediction of acute suicidal ideation in young adults.
Scientific reports
Aug 4, 2021
Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general popu...
Male
Anxiety
Suicide, Attempted
Psychiatric Status Rating Scales
Risk Factors
Young Adult
Adult
Sensitivity and Specificity
Suicidal Ideation
Area Under Curve
Self Concept
Depression
Resilience, Psychological
Surveys and Questionnaires
Adolescent
Humans
Neural Networks, Computer
Mental Disorders
Prognosis
Republic of Korea
Female
Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma.
Scientific reports
May 13, 2021
Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promisi...
Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study.
Journal of medical systems
Mar 1, 2021
Early identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the accepta...
Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer's disease: Machine learning approaches.
Journal of psychopharmacology (Oxford, England)
Feb 15, 2021
BACKGROUND: d-glutamate, which is involved in N-methyl-d-aspartate receptor modulation, may be associated with cognitive ageing.
Male
Middle Aged
Severity of Illness Index
Case-Control Studies
Psychiatric Status Rating Scales
Cognitive Dysfunction
Diagnosis, Differential
Chromatography, High Pressure Liquid
Female
Aged
Aged, 80 and over
Sensitivity and Specificity
Machine Learning
Algorithms
Biomarkers
Humans
Alzheimer Disease
Glutamic Acid
Characterization of specific and distinct patient types in clinical trials of acute schizophrenia using an uncorrelated PANSS score matrix transform (UPSM).
Psychiatry research
Nov 11, 2020
Understanding the specificity of symptom change in schizophrenia can facilitate the evaluation antipsychotic efficacy for different symptom domains. Previous work identified a transform of PANSS using an uncorrelated PANSS score matrix (UPSM) to redu...
Use of machine learning to classify adult ADHD and other conditions based on the Conners' Adult ADHD Rating Scales.
Scientific reports
Nov 2, 2020
A reliable diagnosis of adult Attention Deficit/Hyperactivity Disorder (ADHD) is challenging as many of the symptoms of ADHD resemble symptoms of other disorders. ADHD is associated with gambling disorder and obesity, showing overlaps of about 20% wi...
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