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  1. 1681

    Disruption of Multimodal Brain Networks and Structural-Functional Coupling in Adolescents with Major Depressive Disorder by Wang Y, Wei J, Yan Y, Wang M, Fan H, Du Y, Yang X, Ma X, Ma X

    Published 2025-04-01
    “…Yunhan Wang,1 Jinxue Wei,2 Yushun Yan,2 Min Wang,2 Huanhuan Fan,2 Yue Du,2 Xiao Yang,2 Xiaohong Ma,2 Xiaojuan Ma1 1Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 2Mental Health Center and Institute of Psychiatry, West China Hospital, Sichuan University, Chengdu, People’s Republic of ChinaCorrespondence: Xiaojuan Ma, Email xiaojuanma@126.comBackground: Adolescent MDD has become a significant public health issue, yet its underlying mechanisms remain unclear. Multimodal brain imaging techniques offer a powerful method for exploring complex mental disorders. …”
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  2. 1682

    Multi‐sensor missile‐borne LiDAR point cloud data augmentation based on Monte Carlo distortion simulation by Luda Zhao, Yihua Hu, Fei Han, Zhenglei Dou, Shanshan Li, Yan Zhang, Qilong Wu

    Published 2025-02-01
    “…Firstly, the model of multi‐sensor imaging system is established, taking into account the joint errors arising from the platform itself and the relative motion during the imaging process. …”
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  3. 1683

    Multi-Modal Deep Learning for Lung Cancer Detection Using Attention-Based Inception-ResNet by Mohamed Hosny, Ibrahim A. Elgendy, Mousa Ahmad Albashrawi

    Published 2025-01-01
    “…Deep learning (DL) has emerged as a powerful alternative to autonomously identify complex patterns within radiological and histopathological images. …”
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    Article
  4. 1684

    Magnetic Nanomaterials in Chinese Medicine Chemical Composition Analysis and Drug Metabolism and Its Industry Prospect and Development Path Research by Tengfei Ma, Peng Liu

    Published 2020-01-01
    “…Firstly, the advantages of magnetic nanomaterials and the shortcomings of chemical composition analysis technology of traditional Chinese medicine are analyzed theoretically. …”
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  5. 1685

    Exploring the Effectiveness of Fusing Synchronous/Asynchronous Airborne Hyperspectral and LiDAR Data for Plant Species Classification in Semi-Arid Mining Areas by Yu Tian, Zehao Feng, Lixiao Tu, Chuning Ji, Jiazheng Han, Yibo Zhao, You Zhou

    Published 2025-04-01
    “…However, in semi-arid mining areas characterized by mixed arbor–shrub–herb vegetation, the complex vegetation distribution patterns and spectral features render single-sensor approaches inadequate for achieving fine classification of plant species in such environments. …”
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  6. 1686

    Investigating biomarkers for personality alterations in temporal lobe epilepsy patients: based on peripheral inflammatory indices, electroencephalography, and neuroimaging by Jia Wang, Fuchi Zhang, Yunshan Zhou, Xiulin Zhang, Jianyang Xu, Shouyong Wang, Chengbing Huang, Taipeng Sun, Hugen Xu, Xiangsong Shi

    Published 2025-07-01
    “…BackgroundThe investigation of personality alterations in temporal lobe epilepsy (TLE) constitutes a complex and demanding field of research. These alterations may be intricately linked to neuroinflammation, imaging changes, and electrophysiological irregularities.ObjectiveThis study aims to explore the potential value of the peripheral inflammatory indices, video electroencephalogram (VEEG), hippocampal magnetic resonance imaging (MRI) as biomarkers for personality changes in patients with TLE.MethodsA total of 110 individuals with TLE were categorized into two groups: 55 patients exhibiting personality alterations and 55 patients without personality abnormalities. …”
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  7. 1687
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    Evolution of plastic deformation during multi-pass ECAP of an AA6060 aluminum alloy – An experimental flow line analysis by Nadja Berndt, Nadja A. Reiser, Martin F.-X. Wagner

    Published 2025-01-01
    “…The positions of the indents along several paths, i.e., flow lines, are analyzed from the partially deformed billets using optical images and a graphics software. For the analysis of the material flow we use a phenomenological model that describes the material path along the flow line based on a super-ellipse function, with only one parameter defining the evolution of curvature along the flow line. …”
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  9. 1689
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    Tissue Counter Analysis of Histologic Sections of Melanoma: Influence of Mask Size and Shape, Feature Selection, Statistical Methods and Tissue Preparation by Josef Smolle, Armin Gerger, Wolfgang Weger, Heinz Kutzner, Michael Tronnier

    Published 2002-01-01
    “…Background: Tissue counter analysis is an image analysis tool designed for the detection of structures in complex images at the macroscopic or microscopic scale. …”
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    Semi-Supervised Deep Subspace Embedding for Binary Classification of Sella Turcica by Kaushlesh Singh Shakya, Azadeh Alavi, Julie Porteous, Priti Khatri, Amit Laddi, Manojkumar Jaiswal, Vinay Kumar

    Published 2024-11-01
    “…Perhaps the inherent complexity and variability in the shapes of sella and the lack of advanced assessment tools make the classification of sella challenging, as it requires extensive training, skills, time, and manpower to detect subtle changes that often may not be apparent. …”
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  13. 1693

    Leveraging hybrid model of ConvNextBase and LightGBM for early ASD detection via eye-gaze analysis by Ranjeet Bidwe, Sashikala Mishra, Simi Bajaj, Ketan Kotecha

    Published 2025-06-01
    “…This research introduces a novel method for eye gaze analysis to identify autistic traits in children. This proposed work offers • A novel method of ConvNextBase and LightGBM leveraging eye position as a feature for early detection of autistic traits. • A new ConvNextBase architecture proposed with few unfreezed layers and extra dense layers with units of 512 and 128, respectively, and dropout layers with a rate of 0.5 that extract rich, high-level, and more complex features from the images to improve generalization and mitigate overfitting. • A LightGBM model performed classification using 3-fold cross-validation and found the best parameters for bagging_function, feature_fraction, max_depth, Number_of_leaves and learning_rate with values of 0.8, 0.8, −1, 31 and 0.1 respectively, to improve the model's robustness on unseen data.This proposed method is trained and tested on the publicly available Kaggle dataset, and results are benchmarked with other state-of-the-art methods. …”
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  14. 1694

    AI Efficiency in Dentistry: Comparing Artificial Intelligence Systems with Human Practitioners in Assessing Several Periodontal Parameters by Oana-Maria Butnaru, Monica Tatarciuc, Ionut Luchian, Teona Tudorici, Carina Balcos, Dana Gabriela Budala, Ana Sirghe, Dragos Ioan Virvescu, Danisia Haba

    Published 2025-03-01
    “…Diagnoses were compared against a reference “gold standard” validated by a dental imaging expert and senior clinician. A statistical analysis was performed using SPSS 26.0, applying chi-square tests, ANOVA, and Bonferroni correction to ensure robust results. …”
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