Psychiatry

Lexical meaning is lower-dimensional in psychosis: the intrinsic geometry of the semantic space

Diverse language models (LMs), including large language models (LLMs) based on deep neural networks have come to provide an unprecedented opportunity for mapping out the semantic spaces navigated in speech and their distortions in mental disorders. Recent evidence has pointed to higher mean semantic similarities between words in psychosis, conceptualized as a ‘shrunk’ (more compressed) semantic sp...

Can we detect the undetected? Comparing the prodromes of individuals with first episode psychosis detected and undetected by clinical high risk for psychosis services: an electronic health record study

The majority of first episode psychosis (FEP) patients are undetected (DET-) by clinical high risk for psychosis (CHR-P) services prior to onset and therefore do not receive preventive care for psychosis. We compared features of the psychosis prodrome (symptoms and substance use) between DET- and FEP patients detected by CHR-P services (DET+) to determine whether they share a common prodromal phas...

Enhancing Mental Health Decision-Making with Artificial Intelligence/Machine Learning: A Prescriptive Analytics Approach for Customised Outcomes

Depression is a complex and widespread mental health condition affecting over 280 million people globally, yet access to timely diagnosis and personal...

Conversational AI in Therapy: Current Applications and Future Directions in Mental Health Support

This paper delivers a rigorous mixed-methods synthesis of conversational AI applications in mental health therapy, analyzing 47 randomized controlled ...

Event-based seizure detection in human iEEG with neuromorphic hardware

Epilepsy is a neurological disorder that affects approximately 1% of the global population. The current method for seizure monitoring, seizure diaries...

A Transparent Four-Feature Logistic Model for Depression Screening in Assisted-Living Facilities

Depression in older adults is both common and frequently underdiagnosed, especially in assisted-living communities, where it often co-occurs with mild...

War, Diets, and Mental Health: PTSD in Ukrainian Youth

The ongoing war in Ukraine has exposed young adults to sustained psychological stress, elevating their risk of developing post-traumatic stress disord...

MOKA: A pipeline for multi-omics bridged SNP-set kernel association test

The explosion of genomic and multi-omics data has created a need for scalable, reproducible tools that integrate functional annotations into genome-wi...

Deep learning based treatment remission prediction to transcranial direct current stimulation in bipolar depression using EEG power spectral density

Bipolar disorder is characterized by marked changes in mood and activity levels and is a leading cause of disability worldwide. We sought to investiga...

Leveraging large language models to estimate clinically relevant psychological constructs in psychotherapy transcripts

Developing precise, innocuous markers of psychopathology and the processes that foster effective treatment would greatly advance the field’s ability t...

clickBrick Prompt Engineering: Optimizing Large Language Model Performance in Clinical Psychiatry

Prompt engineering has the potential to enhance large language models’ (LLM) ability to solve tasks through improved in-context learning. In clinical ...

Urinary steroid metabolome shows adrenal, gonadal, and neuroactive steroid dysregulation in adolescents with depression

Steroid hormone profiles in affective disorders suggest hypothalamic– pituitary–adrenal (HPA) axis dysregulation and may reveal novel therapeutic targ...

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 interest to the study of schizophrenia. However, p...

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 diagnosis, and the impact of integrating expert-d...

Prematurity and Genetic Liability for Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by diverse presentations and a strong genetic component. Environmental ...

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 intervention plans and practices. This study identifie...

Portability of an artificial intelligence model for self-harm detection across hospital settings

Adequate self-harm surveillance is a key part of suicide prevention efforts. Our prior work has demonstrated the efficacy of an artificial intelligenc...

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 implications. The rapid development of large language mode...

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 fluctuations in psychological states and behavior....

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 while developing a framework for managing data uncerta...