Latest AI and machine learning research in psychiatry for healthcare professionals.
BackgroundMachine learning offers new avenues for complementing traditional epidemiological approaches by analyzing routinely collected, population-based administrative health data.ObjectiveThis study aimed to identify potential exposomic predictors (hypothesis generation) for Parkinson's disease (PD) across the entire French agricultural workforce.MethodsWe applied XGBoost adapted for Cox proport...
BACKGROUND: There is broad agreement that the onset of bipolar disorders (BD) can be predicted by using combined estimates of familial, genetic and clinical risk. However, there is a lack of consensus about the operationalisation of different risk attributes (e.g., symptoms vs. sub-threshold syndromes; disorder-specific polygenic risk scores [PRS] vs. multiple-disorder PRS dimensions) and their ut...
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social communication deficits and repetitive behaviours. Diagnosing A...
INTRODUCTION: Passive suicidal ideation (SI) is a well-established risk factor for suicidal behavior but has received less attention than active SI. A...
This study explores how machine learning can facilitate large-scale content analysis of suicide-related expressions on social media across cultural co...
Schizophrenia (SCZ) is a highly heritable psychiatric disorder, yet its genetic links with chronic pulmonary diseases remain poorly defined. Such link...
Autism spectrum disorder (ASD) consists of a spectrum of neurodevelopmental conditions characterized by complex behavioural traits and subtle, atypica...
OBJECTIVE: This study aimed to evaluate the quality of GPT-4-generated responses to commonly asked psychosis-related psychoeducational questions from ...
Pharmaceutical poisoning is a major health concern and a leading method of intentional self-poisoning. In Iran, broad medication access has increased ...
OBJECTIVE: The study aimed to quantify types of premature treatment termination in a psychosomatic hospital and to investigate if patient characterist...
To examine dimensional associations between anxiety- and depression-related symptom severity, pain catastrophizing, and resting-state EEG features in ...
Competing risk is a common phenomenon when dealing with time-to-event outcomes in biostatistical applications. An attractive estimand in this setting ...
PURPOSE OF REVIEW: Autism spectrum disorder (ASD) is a neurodevelopmental condition with significant implications for childhood development and public...
BACKGROUND: Rapid population aging and a worsening shortage of care workers necessitate the identification of older adults who require proactive inter...
BACKGROUND: AI has become increasingly used in mental health care for applications such as diagnosis, monitoring, and treatment support. These include...
BACKGROUND: Stress, as commonly recognized, is an integral part of modern life and can significantly affect both mental and physical health. While sub...
OBJECTIVE: OpenAI, the provider of ChatGPT, estimates that approximately 0.15% of weekly active users engage in conversations with the chatbot that co...
BACKGROUND AND PURPOSE: Stroke is a leading cause of disability, associated with impaired motor function and brain connectivity. Mental Simulation Pra...
OBJECTIVE: This study aimed to examine college students' trust in generative artificial intelligence (AI) for mental health information and decisions....
BACKGROUND: Diagnosing autism spectrum disorder (ASD) in adulthood is time-consuming and markedly complicated by the requirement to distinguish betwee...