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robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
based optimization » whale optimization (Expand Search)
lesions based » questions based (Expand Search), lens based (Expand Search), actions based (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
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Showing 1 - 20 results of 139 for search '(( binary based robust optimization algorithm ) OR ( lesions based based optimization algorithm ))', query time: 0.70s Refine Results
  1. 1
    Staging algorithm.

    Staging algorithm. by Atsushi Hamabe (12890022)

    Published 2022
    Subjects: “…pathologically confirmed lesions…”
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  2. 2
    Data_Sheet_1_Optimal therapeutic strategies for pineal region lesions.docx

    Data_Sheet_1_Optimal therapeutic strategies for pineal region lesions.docx by Li-tian Huang (17536452)

    Published 2023
    “…Most importantly, the surgical algorithm for pineal region lesions which was based on preoperatively diagnosis (non-germinoma and germinoma) is useful, especially for developing countries.…”
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  3. 3
    Development of an electronic medical record-based algorithm to identify patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in Japan

    Development of an electronic medical record-based algorithm to identify patients with Stevens-Johnson syndrome and toxic epidermal necrolysis in Japan by Toshiki Fukasawa (7224941)

    Published 2019
    “…We developed a potentially optimized algorithm for identifying SJS/TEN based on clinical practice records. …”
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  4. 4
    Image_2_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG

    Image_2_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG by Li Lu (68660)

    Published 2021
    “…Therefore, we aimed to develop a series of deep learning algorithms and artificial intelligence (AI)–models for automatic PM identification, MM classification, and “Plus” lesion detection based on retinal fundus images.…”
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  5. 5
    Image_3_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG

    Image_3_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG by Li Lu (68660)

    Published 2021
    “…Therefore, we aimed to develop a series of deep learning algorithms and artificial intelligence (AI)–models for automatic PM identification, MM classification, and “Plus” lesion detection based on retinal fundus images.…”
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  6. 6
    Table_1_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.DOCX

    Table_1_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.DOCX by Li Lu (68660)

    Published 2021
    “…Therefore, we aimed to develop a series of deep learning algorithms and artificial intelligence (AI)–models for automatic PM identification, MM classification, and “Plus” lesion detection based on retinal fundus images.…”
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  7. 7
    Image_1_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG

    Image_1_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG by Li Lu (68660)

    Published 2021
    “…Therefore, we aimed to develop a series of deep learning algorithms and artificial intelligence (AI)–models for automatic PM identification, MM classification, and “Plus” lesion detection based on retinal fundus images.…”
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  8. 8
    Image_4_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG

    Image_4_AI-Model for Identifying Pathologic Myopia Based on Deep Learning Algorithms of Myopic Maculopathy Classification and “Plus” Lesion Detection in Fundus Images.JPEG by Li Lu (68660)

    Published 2021
    “…Therefore, we aimed to develop a series of deep learning algorithms and artificial intelligence (AI)–models for automatic PM identification, MM classification, and “Plus” lesion detection based on retinal fundus images.…”
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  9. 9
    Table_1_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.docx

    Table_1_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.docx by Qi Wan (271320)

    Published 2021
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  10. 10
    Table_1_Comparison and analysis of multiple machine learning models for discriminating benign and malignant testicular lesions based on magnetic resonance imaging radiomics.DOCX

    Table_1_Comparison and analysis of multiple machine learning models for discriminating benign and malignant testicular lesions based on magnetic resonance imaging radiomics.DOCX by Yanhui Feng (1484833)

    Published 2023
    “…Objective<p>Accurate identification of testicular tumors through better lesion characterization can optimize the radical surgical procedures. …”
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  11. 11
    DataSheet_2_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.csv

    DataSheet_2_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.csv by Qi Wan (271320)

    Published 2021
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  12. 12
    DataSheet_1_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.csv

    DataSheet_1_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.csv by Qi Wan (271320)

    Published 2021
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  13. 13
    IoU and HD of UNets family when the optimizer is set as Adam. The best-performing results are highlighted using bold font.

    IoU and HD of UNets family when the optimizer is set as Adam. The best-performing results are highlighted using bold font. by Bang-Chuan Chen (21526585)

    Published 2025
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  14. 14
    IoU and HD of UNets family when the optimizer is set as Adagrad. The best-performing results are highlighted using bold font.

    IoU and HD of UNets family when the optimizer is set as Adagrad. The best-performing results are highlighted using bold font. by Bang-Chuan Chen (21526585)

    Published 2025
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  15. 15
    IoU and HD of UNets family when the optimizer is set as Adagrad. The best-performing results are highlighted using bold font.

    IoU and HD of UNets family when the optimizer is set as Adagrad. The best-performing results are highlighted using bold font. by Bang-Chuan Chen (21526585)

    Published 2025
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  16. 16
    Fusion results with UNet2+ (optimizer = Adagrad, learning rate = 0.0001). The best-performing results are highlighted using bold font.

    Fusion results with UNet2+ (optimizer = Adagrad, learning rate = 0.0001). The best-performing results are highlighted using bold font. by Bang-Chuan Chen (21526585)

    Published 2025
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  17. 17
    Summary of the analyzed cases.

    Summary of the analyzed cases. by Atsushi Hamabe (12890022)

    Published 2022
    Subjects: “…pathologically confirmed lesions…”
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  18. 18
    S1 Dataset -

    S1 Dataset - by Atsushi Hamabe (12890022)

    Published 2022
    Subjects: “…pathologically confirmed lesions…”
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  19. 19
    Results of segmentation accuracy.

    Results of segmentation accuracy. by Atsushi Hamabe (12890022)

    Published 2022
    Subjects: “…pathologically confirmed lesions…”
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  20. 20
    Preparation for ground-truth segmentation labels.

    Preparation for ground-truth segmentation labels. by Atsushi Hamabe (12890022)

    Published 2022
    Subjects: “…pathologically confirmed lesions…”
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