Psychiatry

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

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DUNE: a versatile neuroimaging encoder captures brain complexity across three major diseases: cancer, dementia and schizophrenia

Magnetic resonance images (MRI) of the brain exhibit high dimensionality that pose significant chall...

Life Events Extraction From Healthcare Notes for Veteran Acute Suicide Prediction

Predictive models of suicide risk have focused on predictors extracted from structured data found in...

Passive sensing with psyche: utilizing data from wearable technology to predict emotion states

Depression and anxiety are some of the most common mental health disorders in the world contributing...

Predicting Depression in Canadians with or at Risk of Diabetes: A Cross-Sectional Machine Learning Analysis

Depression often goes unrecognized in individuals at risk or living with diabetes, presenting consid...

Identifying clusters of people with Multiple Long-Term Conditions using Large Language Models: a population-based study

Identifying clusters of people with similar patterns of Multiple Long-Term Conditions (MLTC) could h...

Computational Mechanisms of Approach-Avoidance Conflict Predictively Differentiate Between Affective and Substance Use Disorders

Psychiatric disorders are highly heterogeneous and often co-morbid, posing specific challenges for e...

Enhancing Brain Age Estimation Under Uncertainty: A Spectral-normalized Neural Gaussian Process Approach Utilizing 2.5D Slicing

Brain age gap, the difference between estimated brain age and chronological age via magnetic resonan...

Comparative Medical Ecology of Gut Microbiomes in Major Neurodegenerative, Neurodevelopmental, and Psychiatric (NNP) Disorders

This study provides a comprehensive medical ecology analysis of gut microbiome alterations in four n...

Explainable Suicide Phenotyping from Initial Psychiatric Evaluation Notes Using Reasoning Large Language Models

Clinical phenotyping is the process of extracting patient’s observable symptoms and traits to better...

Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders

Biomarker research in psychopathology increasingly employs high-dimensional omics approaches. Yet, p...

Paving the way for precision treatment of psychiatric symptoms with functional connectivity neurofeedback

Major depressive disorder (MDD) remains challenging to treat, with many patients failing to respond ...

Predicting Suicidality in people living with HIV in Uganda: A Machine Learning Approach

People living with HIV (PLWH) are more likely to experience suicidal thoughts and exhibit suicidal b...

Blood Immuno-metabolic Biomarker Signatures of Depression and Affective Symptoms in Young Adults

Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whe...

Machine Learning in Psychiatric Health Records: A Gold Standard Approach to Trauma Annotation

Psychiatric electronic health records present unique challenges for machine learning due to their un...

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