Psychiatry

A large language model-based approach to quantifying the effects of social determinants in liver transplant decisions

Patient life circumstances, including social determinants of health (SDOH), shape both health outcomes and care access, contributing to persistent disparities across gender, race, and socioeconomic status. Liver transplantation exemplifies these challenges, requiring complex eligibility and allocation decisions where SDOH directly influence patient evaluation. We developed an artificial intellig...

Investigation of in vitro neuronal activity processing using a CMOS-integrated ZrO2-based memristive crossbar

The influence of the epileptiform neuronal activity on the response of a CMOS-integrated ZrO2-based memristive crossbar and its conductivity was studied. Epileptiform neuronal activity was obtained in vitro in the hippocampus slices of laboratory mice using 4-aminopyridine experimental model. Synaptic plasticity of the memristive crossbar induced by epileptiform neuronal activity pulses was dete...

Investigating Acoustic-Textual Emotional Inconsistency Information for Automatic Depression Detection

Previous studies have demonstrated that emotional features from a single acoustic sentiment label can enhance depression diagnosis accuracy. Additio...

Leveraging Audio and Text Modalities in Mental Health: A Study of LLMs Performance

Mental health disorders are increasingly prevalent worldwide, creating an urgent need for innovative tools to support early diagnosis and interventi...

Exploring Complex Mental Health Symptoms via Classifying Social Media Data with Explainable LLMs

We propose a pipeline for gaining insights into complex diseases by training LLMs on challenging social media text data classification tasks, obtain...

HAIFAI: Human-AI Interaction for Mental Face Reconstruction

We present HAIFAI - a novel two-stage system where humans and AI interact to tackle the challenging task of reconstructing a visual representation o...

Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder

For the early identification, diagnosis, and treatment of mental health illnesses, the integration of deep learning (DL) and machine learning (ML) h...

Depression detection from Social Media Bangla Text Using Recurrent Neural Networks

Emotion artificial intelligence is a field of study that focuses on figuring out how to recognize emotions, especially in the area of text mining. T...

Fairness in Computational Innovations: Identifying Bias in Substance Use Treatment Length of Stay Prediction Models with Policy Implications

Predictive machine learning (ML) models are computational innovations that can enhance medical decision-making, including aiding in determining opti...

Real-Time Prediction for Athletes' Psychological States Using BERT-XGBoost: Enhancing Human-Computer Interaction

Understanding and predicting athletes' mental states is crucial for optimizing sports performance. This study introduces a hybrid BERT-XGBoost model...

'Debunk-It-Yourself': Health Professionals' Strategies for Responding to Misinformation on TikTok

Misinformation is "sticky" in nature, requiring a considerable effort to undo its influence. One such effort is debunking or exposing the falsity of...

'Being there together for health': A Systematic Review on the Feasibility, Effectiveness and Design Considerations of Immersive Collaborative Virtual Environments in Health Applications

Effectively using immersive multi-user environments for digital applications (via virtual, augmented and mixed reality technologies) beckons the fut...

Advancing Conversational Psychotherapy: Integrating Privacy, Dual-Memory, and Domain Expertise with Large Language Models

Mental health has increasingly become a global issue that reveals the limitations of traditional conversational psychotherapy, constrained by locati...

An ADHD Diagnostic Interface Based on EEG Spectrograms and Deep Learning Techniques

This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) diagnosis by employing deep learning (DL) techniques...

Hierarchical feature extraction on functional brain networks for autism spectrum disorder identification with resting-state fMRI data

Autism Spectrum Disorder (ASD) is a pervasive developmental disorder of the central nervous system, primarily manifesting in childhood. It is charac...

Social Media Data Mining With Natural Language Processing on Public Dream Contents

The COVID-19 pandemic has significantly transformed global lifestyles, enforcing physical isolation and accelerating digital adoption for work, educ...

If Eleanor Rigby Had Met ChatGPT: A Study on Loneliness in a Post-LLM World

Loneliness, or the lack of fulfilling relationships, significantly impacts a person's mental and physical well-being and is prevalent worldwide. Pre...

Predicting Suicides Among US Army Soldiers After Leaving Active Service.

IMPORTANCE: The suicide rate of military servicemembers increases sharply after returning to civilian life. Identifying high-risk servicemembers befor...

Detection of suicidality from medical text using privacy-preserving large language models.

BACKGROUND: Attempts to use artificial intelligence (AI) in psychiatric disorders show moderate success, highlighting the potential of incorporating i...

Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study.

INTRODUCTION: Globally, many people experience mental health difficulties, and the current workforce capacity is insufficient to meet this demand, wit...