Article

Application of Multifeature EEG Analysis and Machine Learning in the Investigation of Neurobiological Mechanisms of Schizophrenia

2026-07-14

Abstract excerpt

<title>Abstract</title> <p>Schizophrenia (SC) is a severe mental disorder characterized by complex pathological mechanisms and clinical manifestations, which poses significant challenges for diagnosis and treatment. This study aimed to explore the neural mechanism abnormalities in patients with SC through electroencephalogram (EEG) signal analysis and develop an efficient intelligent diagnostic model. EEG data we...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 457f89a2-09c9-51d8-ae87-403d5fc856d5
DOI: 10.21203/rs.3.rs-10122436/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Application of Multifeature EEG Analysis and Machine Learning in the Investigation of Neurobiological Mechanisms of SchizophreniaDOI 10.21203/rs.3.rs-10122436/v1Read

A Fused Power Spectrum based Feature Selection to Identify Schizophrenia from EEG Signals using Deep Learning Models - An Experimental StudySemantic proximity Read

A Generalizable Efficient Machine Learning Framework for Schizophrenia Classification Using Multiscale EEG Features and Ensemble MethodsSemantic proximity Read

The EEG multiverse of schizophreniaSemantic proximity Read

Enhancing Prediction of Individualized Antipsychotic Outcome with fMRI-EEG Feature Integration in First-Episode Schizophrenia: A Real-World StudySemantic proximity Read

Prediction of antipsychotic drug efficacy for schizophrenia treatment based on neural features of the resting-state functional connectomeSemantic proximity Read

Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning ApproachSemantic proximity Read

A Novel Deep Learning Approach for Bipolar Disorder Classification via Quantitative EEGSemantic proximity Read

Machine Learning based identification of suicidal risk in patients with schizophrenia using multi-level resting state fMRI featuresSemantic proximity Read

Reproducible abnormalities of functional gradient reliably predict clinical and cognitive symptoms in schizophreniaSemantic proximity Read

Feature-Optimized Hybrid AI Models for Explainable and Generalizable Epilepsy PredictionSemantic proximity Read

Classification of schizophrenia spectrum disorder using machine learning and functional connectivity: reconsidering the clinical applicationSemantic proximity Read

Deep Learning Versus Classical Machine Learning for Schizophrenia Detection from EEG: A Cross-Dataset Generalization StudySemantic proximity Read