Psychiatry

Schizophrenia

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

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Lurasidone uses and dosages in Spain: RETROLUR, a real-world retrospective analysis using artificial intelligence.

INTRODUCTION: Lurasidone is used for schizophrenia and bipolar depression in many countries, yet the...

Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.

Previous deep learning-based brain network research has made significant progress in understanding t...

Preliminary investigation of an artificial intelligence-based cognitive behavioral therapy training tool.

We developed an asynchronous online cognitive behavioral therapy (CBT) training tool that provides a...

A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.

Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality ...

Predicting conversion to psychosis using machine learning: response to Cannon.

BACKGROUND: We previously reported that machine learning could be used to predict conversion to psyc...

Multi-center brain age prediction via dual-modality fusion convolutional network.

Accurate prediction of brain age is crucial for identifying deviations between typical individual br...

MO-GCN: A multi-omics graph convolutional network for discriminative analysis of schizophrenia.

The methodology of machine learning with multi-omics data has been widely adopted in the discriminat...

Applied pharmacogenetics to predict response to treatment of first psychotic episode: study protocol.

The application of personalized medicine in patients with first-episode psychosis (FEP) requires too...

DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusi...

Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders.

DNA methylation (DNAm) is essential for brain development and function and potentially mediates the ...

On the improvement of schizophrenia detection with optical coherence tomography data using deep neural networks and aggregation functions.

Schizophrenia is a serious mental disorder with a complex neurobiological background and a well-defi...

Machine learning prediction model of the treatment response in schizophrenia reveals the importance of metabolic and subjective characteristics.

Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic a...

How can language models assist with pharmaceuticals manufacturing deviations and investigations?

Large Language Models (LLM) such as the Generative-Pretrained-Transformer (GPT) and Large-Language-M...

A novel ECG-based approach for classifying psychiatric disorders: Leveraging wavelet scattering networks.

Individuals with neuropsychiatric disorders experience both physical and mental difficulties, hinder...

Predictive utility of artificial intelligence on schizophrenia treatment outcomes: A systematic review and meta-analysis.

Identifying optimal treatment approaches for schizophrenia is challenging due to varying symptomatol...

AI-based medication adherence prediction in patients with schizophrenia and attenuated psychotic disorders.

OBJECTIVE: The capacity of machine-learning algorithms to predict medication adherence was assessed ...

Functional Connectivity Biomarker Extraction for Schizophrenia Based on Energy Landscape Machine Learning Techniques.

Brain connectivity represents the functional organization of the brain, which is an important indica...

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