Psychiatry

RIPTOSO: The development of a screening tool for adverse events during forensic-psychiatric inpatient treatments of offenders with schizophrenia spectrum disorders.

Adverse events such as compulsory measures, absconding, illicit substance use, self-harm, aggressive...

Investigating the interpretability of ChatGPT in mental health counseling: An analysis of artificial intelligence generated content differentiation.

The global impact of COVID-19 has caused a significant rise in the demand for psychological counseli...

Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data.

Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and ...

Prediction of remission of pharmacologically treated psychotic depression: A machine learning approach.

BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment...

Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.

BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its...

Emotion Recognition in Older Adults with Quantum Machine Learning and Wearable Sensors

We investigate the feasibility of inferring emotional states exclusively from physiological signal...

Beyond Scale: Small Language Models are Comparable to GPT-4 in Mental Health Understanding

The emergence of Small Language Models (SLMs) as privacy-preserving alternatives for sensitive app...

Development and Evaluation of HopeBot: an LLM-based chatbot for structured and interactive PHQ-9 depression screening

Static tools like the Patient Health Questionnaire-9 (PHQ-9) effectively screen depression but lac...

Modeling the Determinants of Subjective Well-Being in Schizophrenia.

BACKGROUND: The ultimate goal of successful schizophrenia treatment is not just to alleviate psychot...

Prediction of Adolescent Suicide Attempt by Integrating Clinical, Neurocognitive and Geocoded Neighborhood Environment Data.

BACKGROUND AND HYPOTHESIS: Suicide attempt is a complex behavior influenced by a combination of fact...

Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery

In this paper, we investigate a practical yet challenging task: On-the-fly Category Discovery (OCD...

A Dopamine-Serotonin Theory of Consciousness

This work presents a comprehensive theory of consciousness grounded in mathematical formalism and ...

Exploring a Hybrid Deep Learning Approach for Anomaly Detection in Mental Healthcare Provider Billing: Addressing Label Scarcity through Semi-Supervised Anomaly Detection

The complexity of mental healthcare billing enables anomalies, including fraud. While machine lear...

Incorporating end-user perspectives into the development of a machine learning algorithm for first time perinatal depression prediction.

OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental healt...

Prenatal exposure to criteria air pollution and traffic-related air toxics and risk of autism spectrum disorder: A population-based cohort study of California births (1990-2018).

BACKGROUND: Autism spectrum disorder (ASD) prevalence has risen steadily in California (CA) over sev...

Distinct processing stages of cross-modal conflict in schizophrenia: The role of auditory cortex underactivation.

BACKGROUND: The cross-modal conflict deficit is a key feature of schizophrenia. However, it remains ...

Beyond total scores: Enhancing psychotherapy outcome prediction with item-level scores.

OBJECTIVE: This study aims at improving dropout and treatment nonresponse prevention by optimizing t...

Artificial intelligence in autism spectrum disorder: A path to early detection and improved outcomes.

Identifying metabolites of new psychoactive substances using in silico prediction tools.

New psychoactive substances (NPS) pose an increasing challenge for clinical and forensic toxicology ...

Machine learning-based prediction of anxiety disorders using blood metabolite and social trait data from the UK Biobank.

Anxiety disorders are the most prevalent type of mental health disorders and are characterised by ex...

Evaluating natural language processing derived linguistic features associated with current suicidal ideation, past attempts, and future suicidal behavior.

BACKGROUND: People with psychosis have a higher suicide risk than the general population. Natural la...