Schizophrenia

Large language models in implant dentistry: a scoping review of applications, performance, and limitations.

BACKGROUND: This scoping review evaluates the current state of generative artificial intelligence (AI) in implant dentistry, focusing on the performance, clinical applications, and inherent limitations of large language models (LLMs) in both clinical and educational settings. METHODS: A scoping review was conducted in accordance with PRISMA-ScR guidelines. A comprehensive search across four electr...

Large Language Model Responses to Common Otolaryngological Questions: Evaluating Accuracy, Appropriateness, Readability, and Hallucinations.

OBJECTIVES: Artificial Intelligence (AI) is increasingly integrated into medicine, including otolaryngology. However, concerns remain regarding the accuracy of generated content and the tendency of large language models (LLMs) to fabricate references. This study evaluates the accuracy, appropriateness, readability, and hallucination of references in 2 prevalent large language models, ChatGPT and C...

The impact of GenAI-assisted instructional design on the teaching ability of pre-service physical education teachers.

In view of a pain point in the field of textual logic generation and physiological load quantification in physical education (PE) instructional design...

A survey of deep learning techniques in detecting neurological disorders using MRI.

Magnetic resonance imaging (MRI) is widely regarded as the most reliable non-invasive imaging modality for detecting neurological disorders. However, ...

Agentic Artificial Intelligence for the Automated Generation of Accurate Summary Podcasts of Radiology Research Papers.

OBJECTIVE: To evaluate whether a custom agentic artificial intelligence (AI) pipeline can overcome the limitations of general-purpose large language m...

Ambient AI Scribes to Create Educational Feedback Notes for Medical Students: Randomized Trial.

BACKGROUND: High-quality observation and feedback contribute to the development of clinical competence and professional growth in medical education. F...

Capturing multi-disease states on a spectrum with machine learning and routine clinical data.

BACKGROUND: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, and clinical manifestations. It is unknown whether t...

Development and evaluation of an effective solubility prediction model for pharmaceuticals in organic solvents using machine learning based on eXtreme Gradient Boosting.

In this work, we have examined the predictive capability of a machine leaning model based on the XGBoost framework as regards the solubility of active...

Large Language Model-Generated Patient Instructions for Prescriptions in Primary Health Care: Preclinical Algorithm Validation.

BACKGROUND: The application of generative artificial intelligence to simplify medication use instructions has the potential to enhance people's health...

Feasibility and challenges of large language model (LLM)-generated neonatal resuscitation simulations: a multicenter exploratory study.

BACKGROUND: Simulation-based training (SBT) in neonatal resuscitation has positive impact on educational and neonatal outcomes. However, the implement...

Executive function profiles identify stable schizophrenia subtypes with distinct symptoms, biological markers and treatment responses: a cross-time clustering and validation study.

BACKGROUND: Executive function (EF) is a heterogeneous neuropsychological construct, and impairments in EF dimensions represent a core aspect of psych...

Suicide and self-harm in the age of generative artificial intelligence: The case of ChatGPT and rise of suicide-related lawsuits.

Self-harm and suicide trends have taken a new turn in the era of GenAI and communicative chatbots. Recent OpenAI's own report suggests that 1.2 millio...

Convenience or risk? Understanding users' continuance intention toward AI health assistants.

In recent years, AI health assistants have rapidly proliferated in the field of personal health management, yet systematic explanations of the mechani...

Vision-language models as an integrative layer for clinical artificial intelligence in radiology: A systems-level perspective.

Clinical adoption of artificial intelligence (AI) in radiology has matured through task-specific tools for detection, segmentation, triage, and quanti...

Combining Anti-Hallucination Strategies for Reliable LLM-Based Clinical Information Extraction.

We present a novel LLM-based approach for medical concept extraction that combines multiple anti-hallucination strategies. Our Streamlit web applicati...

Decoding shared pathogenic networks of oxidative stress in neuropsychiatric disorders to prioritize multi-target therapeutics from natural products.

BACKGROUND: Neurodegenerative and psychiatric disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and ...

Inhibitory control deficits and ventral attention network alterations linked to apathy in schizophrenia.

Individuals with schizophrenia demonstrated impaired inhibitory control and apathy symptoms, which are characterized by a reduction in self-initiated ...

Hallucination risk and trustworthiness of generative AI systems based on IVMPF-MABAC decision-making strategies.

Hallucination risk and trustworthiness of a generative artificial intelligence system play an important and vital role in daily-life scenarios. The te...

A temporally Anchored Retrieval-Augmented Generation Framework for Metabolic and Bariatric Surgery Patient Education: An IFSO Artificial Intelligence Task Force Multinational Validation Study.

BACKGROUND: Large language models (LLMs) offer promising tools for patient education, yet fixed knowledge cutoffs and hallucination risk limit their c...

Large Language Models in Clinical Trial Recruitment: Sociotechnical and Economic Framework Development Study.

BACKGROUND: Large language models (LLMs) have shown substantial promise in patient-trial matching, but most published studies still evaluate the perfo...