Showing 61 - 80 results of 589 for search 'T38 (classification)', query time: 0.05s Refine Results
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    Predictive value of myositis antibodies: role of semiquantitative classification and positivity for more than one autoantibody by Anne M Kerola, Arno Hänninen, Annukka Pietikäinen, Julia Barantseva, Annaleena Pajander

    Published 2025-01-01
    “…The PPV for malignancy was highest for anti-TIF1-γ (38%), followed by anti-PL-7 (32%). Stronger antibody band intensity was associated with higher PPVs for myositis and CTD but not for ILD or malignancies. …”
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    Postoperative symptom changes following uterine artery embolization for uterine fibroid based on FIGO classification by Yoshimi Nozaki, Shiori Takeuchi, Masafumi Arai, Yoshiki Kuwatsuru, Hiroshi Toei, Shingo Okada, Hitomi Kato, Naoko Saito, Takamichi Nobushima, Keisuke Murakami, Mari Kitade, Ryohei Kuwatsuru

    Published 2025-01-01
    “…Abstract Background Classifying uterine fibroid using the International Federation of Gynecology and Obstetrics (FIGO) classification system assists treatment decision-making and planning. …”
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    Feasibility of the International Caries Classification and Management System (ICCMS) Protocol in a Hospital-Based Setting in India by Imam Azam, Vijay P. Mathur, Nitesh Tewari, Rahul Morankar, Kalpana Bansal, Anju Rajwar

    Published 2024-11-01
    “…Objective: To evaluate the feasibility of the International Caries Classification and Management System (ICCMS) protocol in a hospital-based setting in India. …”
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    Automated orthodontic diagnosis via self-supervised learning and multi-attribute classification using lateral cephalograms by Qiao Chang, Yuxing Bai, Shaofeng Wang, Fan Wang, Shuang Liang, Xianju Xie

    Published 2025-02-01
    “…Additionally, a multi-attribute classification network is proposed, leveraging attribute correlations to optimize parameters and enhance classification performance. …”
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    Integrating deformable CNN and attention mechanism into multi-scale graph neural network for few-shot image classification by Yongmin Liu, Fengjiao Xiao, Xinying Zheng, Weihao Deng, Haizhi Ma, Xinyao Su, Lei Wu

    Published 2025-01-01
    “…Compared with the benchmark model, the classification accuracy has increased by 1.07% and 1.33% respectively; In the 5-way 5-shot task, the classification accuracy of the mini-ImageNet dataset was improved by 11.41%, 7.42%, and 5.38% compared to GNN, TPN, and dynamic models, respectively. …”
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    Remote Sensing Scene Classification using ConvNeXt-Tiny Model with Attention Mechanism and Label Smoothing by Rachmawan Atmaji Perdana, Aniati Murni Arimurthy, Risnandar

    Published 2024-06-01
    “…The experiments in this study also aim to prove that the integration of the attention module and LSR into the basic CNN network can improve precision, because the attention module can strengthen important features and weaken features that are less useful for classification. The experimental results proved that the integration of ECANet and LSR in the ConvNeXt-Tiny base network obtained a higher precision of 0.38% in the UC-Merced dataset, 0.7% in the AID, and 0.4% in the WHU-RS19 dataset than the ConvNeXt-Tiny model without ECANet and LSR. …”
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