Brain Informatics
Brain Informatics(英文缩写 BRAIN INFORM),ISSN 2198-4018,eISSN 2198-4026 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
指标来源：jcr_cas_ifqb
期刊简介
暂无简介。
历年影响因子趋势
| 年份 | 影响因子 | JCR 分区 |
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| - | Q1 | |
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Brain Informatics 最新收录文献
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Brain dysconnectivity patterns associated with chronic back pain development.
Chronic back pain often emerges from a transitional period of subacute pain, yet no clinically applicable biomarker exists to identify which patients are at risk for chronification. Evidence suggests …
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CAE-BrainNet: a statistically validated class-adaptive attention ensemble model for explainable brain tumor classification from MRI.
Deep learning has further accelerated progress in automated Magnetic Resonance Imaging (MRI) based classification of brain tumors, whereas prior studies have often reflected critical limitations such …
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Investigating functional brain networks in multiple sclerosis patients: a graph theory approach for evaluating working memory impairment.
This study introduces a graph theory-based machine learning framework to analyze functional brain networks in Multiple Sclerosis (MS) patients during working memory tasks. Using fMRI data from 22 part…
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Adaptive frequency band attention-guided CNN-BiLSTM for Spatial-Spectral-Temporal EEG emotion recognition.
Electroencephalography (EEG)-based emotion recognition has gained increasing attention in affective computing because EEG provides high temporal resolution and reflects intrinsic neural activity. Howe…
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Effiformer: a unified data-efficient vision transformer-CNN framework for interpretable epileptic seizure detection.
Epileptic seizures are short episodes of abnormal electrical activity in the brain that can cause convulsions, loss of consciousness, and other similar symptoms. Despite therapy, around 30% of patient…
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Decoding neuronal gene expression: integrative insights from omics and AI.
Neuronal functional diversity and pathological vulnerability are governed by multi-layered regulatory programs. While high-throughput omics and neuroimaging provide high-resolution snapshots of these …
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Hybrid self-supervised EEG emotion representation: masked reconstruction joint with mutual information bounds.
EEG signals are widely used in affective computing and brain informatics for emotion recognition due to their non-invasiveness. Deep learning and self-supervised learning (SSL) are key for EEG represe…
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EEG-DBNet: a dual-branch framework for temporal-spectral representation learning of motor imagery electroencephalography.
Motor imagery electroencephalography (MI-EEG) decoding remains challenging due to low signal-to-noise ratio and complex temporal-spectral characteristics. This study aims to develop a robust deep lear…
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Cross-attention-guided subject-adaptive graph learning for multimodal autism classification: integrating structural and functional MRI data.
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by structural atypicality and abnormal functional connectivity. It remains challenging to accurately delineate an ASD-as…
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Generalizable and explainable deep learning for brain MRI: a multi-cohort evaluation of 3D architectures for age and sex prediction.
Deep learning (DL) methods increasingly outperform classical approaches in brain MRI analysis, yet their generalizability across independent imaging cohorts remains insufficiently evaluated. Because a…