Psychiatry

Schizophrenia

Latest AI and machine learning research in schizophrenia for healthcare professionals.

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Showing 1009-1029 of 2,684 articles
Information Leakage and Performance Overestimation in EEG-Based Schizophrenia Detection: Evidence from Literature and Empirical Analyses

Detecting schizophrenia (SZ) from electroencephalography (EEG) signals using machine- and deep learn...

Large Language Models for Thematic Analysis in Healthcare Research: A Blinded Mixed-Methods Comparison with Human Analysts

Large language models (LLMs) are increasingly used for qualitative thematic analysis, yet evidence o...

Evaluation of large language model chatbot responses to psychotic prompts

The large language model (LLM) chatbot product ChatGPT has accumulated 800 million weekly users sinc...

A medically grounded LLM agent–based tool to detect patient safety events in medical records

Large language models (LLMs) have shown incredible promise in medicine. While LLMs may be particular...

TRUSTING: An International Multicenter Observational Study of Speech-Based Relapse Prediction in Psychosis Using Explainable AI

The course of psychotic disorders typically involves relapses. Early warning signs vary between indi...

IllusionBench: A Large-scale and Comprehensive Benchmark for Visual Illusion Understanding in Vision-Language Models

Current Visual Language Models (VLMs) show impressive image understanding but struggle with visual...

Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.

IMPORTANCE: Cognitive functioning is associated with various factors, such as age, sex, education, a...

Jan 2025 39382875
Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning.

PURPOSE: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This ...

Jan 2025 39740776
Semantic abnormalities in schizophrenia and bipolar disorder: A natural language processing approach.

INTRODUCTION: The diagnostic boundaries between schizophrenia and bipolar disorder are controversial...

Jan 2025 39846293
Towards a Systematic Evaluation of Hallucinations in Large-Vision Language Models

Large Vision-Language Models (LVLMs) have demonstrated remarkable performance in complex multimoda...

Is Your Text-to-Image Model Robust to Caption Noise?

In text-to-image (T2I) generation, a prevalent training technique involves utilizing Vision Langua...

An End-to-End Depth-Based Pipeline for Selfie Image Rectification

Portraits or selfie images taken from a close distance typically suffer from perspective distortio...

MedHallBench: A New Benchmark for Assessing Hallucination in Medical Large Language Models

Medical Large Language Models (MLLMs) have demonstrated potential in healthcare applications, yet ...

Extract Free Dense Misalignment from CLIP

Recent vision-language foundation models still frequently produce outputs misaligned with their in...

Multimodal Preference Data Synthetic Alignment with Reward Model

Multimodal large language models (MLLMs) have significantly advanced tasks like caption generation...

AlzheimerRAG: Multimodal Retrieval Augmented Generation for PubMed articles

Recent advancements in generative AI have flourished the development of highly adept Large Languag...

Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage

Multimodal large language models (MLLMs) excel at generating highly detailed captions but often pr...

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