Schizophrenia

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...

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...

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 Case of Artificial Intelligence Chatbot Hallucination.

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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...

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

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...

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...

Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations.

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

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...

Fingerprints as Predictors of Schizophrenia: A Deep Learning Study.

BACKGROUND AND HYPOTHESIS: The existing developmental bond between fingerprint generation and growth...

Qualitative and Artificial Intelligence-Based Sentiment Analysis of Turkish Tweets Related to Schizophrenia.

OBJECTIVE: The aim of this study was to qualitatively examine Turkish tweets about schizophrenia in ...

Translating Natural Language Processing into Mainstream Schizophrenia Assessment.

Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation.

BACKGROUND AND HYPOTHESIS: Despite decades of "proof of concept" findings supporting the use of Natu...

Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.

BACKGROUND: Validated clinical prediction models of short-term remission in psychosis are lacking. O...

Implementation of a machine learning algorithm for automated thematic annotations in avatar: A linear support vector classifier approach.

Avatar Therapy (AT) is a modern therapeutic alternative for patients with schizophrenia suffering fr...

Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data.

In the modern world, with so much inherent stress, mental health disorders (MHDs) are becoming more ...

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Artificial intelligence, such as deep generative methods, represents a promising solution to de novo...