AFM-DViT: A framework for IoT-driven medical image analysis
With the rise of Internet of Things (IoT) in healthcare, automated medical image analysis has become essential for real-time disease detection. However, current models face limitations in handling diverse datasets and ensuring privacy across distributed systems. To address these challenges, we propo...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016824012833 |
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| author | Jiacheng Yang |
| author_facet | Jiacheng Yang |
| author_sort | Jiacheng Yang |
| collection | DOAJ |
| description | With the rise of Internet of Things (IoT) in healthcare, automated medical image analysis has become essential for real-time disease detection. However, current models face limitations in handling diverse datasets and ensuring privacy across distributed systems. To address these challenges, we propose the AFM-DViT model, which integrates adaptive federated learning with Vision Transformer, significantly enhancing diagnostic accuracy and efficiency in IoT-based settings. Our framework not only improves detection capabilities but also effectively addresses critical issues related to data privacy and heterogeneity in medical imaging. Experimental results demonstrate that AFM-DViT outperforms state-of-the-art methods by achieving an AUROC of 0.841 and sensitivity of 0.925 on the ChestX-ray14 dataset, alongside a sensitivity of 0.888 with an AUC of 0.905 on the LUNA16 dataset. These results highlight the model’s robust detection accuracy while maintaining data privacy. The AFM-DViT model offers an effective solution for secure and efficient medical image analysis in IoT-enabled environments. |
| format | Article |
| id | doaj-art-5e51d51e38ba4aa1b127c1fdc91a6ab2 |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-5e51d51e38ba4aa1b127c1fdc91a6ab22025-02-07T04:46:57ZengElsevierAlexandria Engineering Journal1110-01682025-02-01113294305AFM-DViT: A framework for IoT-driven medical image analysisJiacheng Yang0School of Information Engineering and Artificial Intelligence, Lanzhou University of Finance and Economics, Lanzhou, 730101, ChinaWith the rise of Internet of Things (IoT) in healthcare, automated medical image analysis has become essential for real-time disease detection. However, current models face limitations in handling diverse datasets and ensuring privacy across distributed systems. To address these challenges, we propose the AFM-DViT model, which integrates adaptive federated learning with Vision Transformer, significantly enhancing diagnostic accuracy and efficiency in IoT-based settings. Our framework not only improves detection capabilities but also effectively addresses critical issues related to data privacy and heterogeneity in medical imaging. Experimental results demonstrate that AFM-DViT outperforms state-of-the-art methods by achieving an AUROC of 0.841 and sensitivity of 0.925 on the ChestX-ray14 dataset, alongside a sensitivity of 0.888 with an AUC of 0.905 on the LUNA16 dataset. These results highlight the model’s robust detection accuracy while maintaining data privacy. The AFM-DViT model offers an effective solution for secure and efficient medical image analysis in IoT-enabled environments.http://www.sciencedirect.com/science/article/pii/S1110016824012833Adaptive federated learningVision transformerIoTMedical image analysisPrivacy preservation |
| spellingShingle | Jiacheng Yang AFM-DViT: A framework for IoT-driven medical image analysis Alexandria Engineering Journal Adaptive federated learning Vision transformer IoT Medical image analysis Privacy preservation |
| title | AFM-DViT: A framework for IoT-driven medical image analysis |
| title_full | AFM-DViT: A framework for IoT-driven medical image analysis |
| title_fullStr | AFM-DViT: A framework for IoT-driven medical image analysis |
| title_full_unstemmed | AFM-DViT: A framework for IoT-driven medical image analysis |
| title_short | AFM-DViT: A framework for IoT-driven medical image analysis |
| title_sort | afm dvit a framework for iot driven medical image analysis |
| topic | Adaptive federated learning Vision transformer IoT Medical image analysis Privacy preservation |
| url | http://www.sciencedirect.com/science/article/pii/S1110016824012833 |
| work_keys_str_mv | AT jiachengyang afmdvitaframeworkforiotdrivenmedicalimageanalysis |