Psychiatry

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

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Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.

INTRODUCTION: Post-stroke depression is one of the important complications of stroke and affects pat...

The effect of esketamine on perioperative anxiety and depressive symptoms in patients undergoing total hysterectomy.

AIM: This study aimed to evaluate the effect of esketamine on perioperative anxiety and depressive s...

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machi...

The rise of artificial intelligence for cognitive behavioral therapy: A bibliometric overview.

Recent years have seen a sharply rising interest in the scientific area dedicated to the study of th...

Unveiling Public Stigma for Borderline Personality Disorder: A Comparative Study of Artificial Intelligence and Mental Health Care Providers.

Generative artificial intelligence (GAI) programs can identify symptoms and make recommendations for...

Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning.

IMPORTANCE: The diagnosis of schizophrenia and bipolar disorder is often delayed several years despi...

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and e...

Application of artificial intelligence (AI) in the creation of discharge summaries in psychiatric clinics.

BackgroundThe integration of artificial intelligence (AI; ChatGPT 4.0) into medical workflow present...

Do positive psychosocial factors contribute to the prediction of coronary artery disease? A UK Biobank-based machine learning approach.

AIMS: Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural ri...

[Construction of recognition models for subthreshold depression based on multiple machine learning algorithms and vocal emotional characteristics].

OBJECTIVES: To construct vocal recognition classification models using 6 machine learning algorithms...

Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health.

Previous research has established type 2 diabetes mellitus as a significant risk factor for various ...

Neural dynamics of mental state attribution to social robot faces.

The interplay of mind attribution and emotional responses is considered crucial in shaping human tru...

Using Machine Learning to Predict Uptake to an Online Self-Guided Intervention for Stress During the COVID-19 Pandemic.

Online self-guided interventions appear efficacious for alleviating some mental health concerns. How...

Generative AI and the profession of genetic counseling.

The development of artificial intelligence (AI) including generative large language models (LLMs) an...

A Framework for Comparison and Interpretation of Machine Learning Classifiers to Predict Autism on the ABIDE Dataset.

Autism is a neurodevelopmental condition affecting ~1% of the population. Recently, machine learning...

Eye Movement Characteristics for Predicting a Transition to Psychosis: Longitudinal Changes and Implications.

BACKGROUND AND HYPOTHESIS: Substantive inquiry into the predictive power of eye movement (EM) featur...

Key Predictors of Generativity in Adulthood: A Machine Learning Analysis.

OBJECTIVES: This study aimed to explore a broad range of predictors of generativity in older adults....

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