Psychiatry

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

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An ensemble multimodal approach for predicting first episode psychosis using structural MRI and cognitive assessments

Classification between first episode psychosis (FEP) patients and healthy controls is of particular ...

Integrating Expert Knowledge into Large Language Models Improves Performance for Psychiatric Reasoning and Diagnosis

The authors sought to evaluate the performance of common large language models (LLMs) in psychiatric...

Prematurity and Genetic Liability for Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by diverse presentati...

Patterns of Suicidal Stress Disclosure on Social Media: Integrating Computational and Qualitative Approaches

The lack of understanding of how individuals communicate suicidal stress hinders global suicide inte...

MentalQLM: A lightweight large language model for mental healthcare based on instruction tuning and dual LoRA modules

Mental disorders pose significant challenges to healthcare systems and have profound social implicat...

Computational network models for forecasting and control of mental health trajectories in digital applications

Ecological momentary assessments (EMA) have transformed mobile mental health by capturing real-time ...

Managing Data Uncertainty and Machine Learning for Adult ADHD Classification Using Accelerometry: OBF-Psychiatric Case Study

This study aims to enhance our understanding of ADHD individuals through accelerometer analysis whil...

Leveraging Large Language Models and Patient Portal Messages for Early Identification of Depression

Large language model (LLM)-assisted early warning system may help overcome existing barriers to time...

Artificial Intelligence-based Automated Echocardiographic Analysis and the Workflow of Sonographers: A randomized crossover trial

This randomized crossover trial aimed to evaluate whether an artificial intelligence (AI)-based auto...

Sleep as a Modifiable Risk Factor for Childhood Autism: Stratified Analysis of U.S. National Survey of Children’s Health Data

This study aimed to examine the association between age-specific sleep sufficiency and autism spectr...

Reading Between the Signs: Predicting Future Suicidal Ideation from Adolescent Social Media Texts

Suicide is a leading cause of death among adolescents (aged 12–18), yet predicting it remains a sign...

Developing an AI-Enhanced Individualized Prediction Tool for Psychopathological Symptoms in Vietnam: A Study Protocol

Artificial intelligence (AI) is increasingly leveraged in mental healthcare for early detection, mon...

Neuroimaging Correlates of Post-Stroke Pain After Ischemic Stroke: Secondary Analysis of the INSPiRE-TMS Trial

Post-stroke pain (PSP) affects nearly half of stroke survivors, severely compromising quality of lif...

Machine learning based prediction of high school student mental health

Recent increases in the prevalence rates of anxiety, depression, and suicidal ideation, especially i...

Identifying Key Predictive Features for Opioid Use Disorder Using Machine Learning

Opioid Use Disorder (OUD) continues to pose a pressing public health challenge across the United Sta...

Multimodal Speech and Text Models to Detect Suicidal Risks in Adolescents

Early detection of suicide risk in adolescents is crucial but faces challenges including stigma, rel...

Predicting Mental and Psychomotor Delay in Very Pre-term Infants using Large Language Models

Very preterm infants face a considerably higher risk of neurodevelopmental delays, making early diag...

Predicting Olanzapine Induced BMI increase using Machine Learning on population-based Electronic Health Records

Weight gain is a common side effect in patients treated with olanzapine (N05AH03), contributing to i...

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