Schizophrenia

HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning

Hallucination has been a major problem for large language models and remains a critical challenge ...

Transforming nursing with large language models: from concept to practice.

Large language models (LLMs) such as ChatGPT have emerged as potential game-changers in nursing, aid...

MeMemo: On-device Retrieval Augmentation for Private and Personalized Text Generation

Retrieval-augmented text generation (RAG) addresses the common limitations of large language model...

Classification of Schizophrenia using Intrinsic Connectivity Networks and Incremental Boosting Convolution Neural Networks.

One of the key challenges in the use of resting brain functional magnetic resonance imaging (fMRI) n...

A Cross-Feature Mutual Learning Framework to Integrate Functional Connectivity and Activity for Brain Disorder Classification.

Time courses (TC) and functional network connectivity (FNC) features, derived from functional magnet...

Label Noise-Robust Ensemble Deep Multimodal Framework For Neuroimaging Data.

Neuroimaging data have become widely studied in the context of identifying brain-based markers of me...

Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach.

The diagnosis of schizophrenia (SZ) can be challenging due to its diverse symptom presentation. As s...

Evaluating RAG-Fusion with RAGElo: an Automated Elo-based Framework

Challenges in the automated evaluation of Retrieval-Augmented Generation (RAG) Question-Answering ...

Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images

Schizophrenia is a debilitating, chronic mental disorder that significantly impacts an individual'...

Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging

Neural networks, whice have had a profound effect on how researchers study complex phenomena, do s...

A Case of Artificial Intelligence Chatbot Hallucination.

Genetic Bottleneck and the Emergence of High Intelligence by Scaling-out and High Throughput

We study the biological evolution of low-latency natural neural networks for short-term survival, ...

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This review delves into the possible role of artificial intelligence (AI) in medical research, from ...

Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis.

Novel features derived from imaging and artificial intelligence systems are commonly coupled to cons...

Clinical Information Extraction with Large Language Models: A Case Study on Organ Procurement.

Recent work has demonstrated that large language models (LLMs) are powerful tools for clinical infor...

Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN).

BACKGROUND: Connectome is understanding the complex organization of the human brain's structural and...

On the 'Hallucinations' of Artificial Intelligence and the Hallucination Experience in Human.

Real-Time Detection of Emotions Based on Facial Expression for Mental Health.

When it comes to health, a very widespread problem nowadays is mental health, where almost 18% of th...

Is ChatGPT a "Fire of Prometheus" for Non-Native English-Speaking Researchers in Academic Writing?

Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential...

A Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data.

Understanding the structural and functional mechanisms of the brain is challenging for mood and ment...

Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations.

Identifying subtypes of neuropsychiatric disorders based on characteristics of their brain activity ...