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Radiology. Artificial Intelligence
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June 12, 2024
Vision Transformer-based Deep Learning Models Accelerate Further Research for Predicting Neurosurgical Intervention
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Radiology
|
February 13, 2024
Transformer Unlocks the Gateway to Advanced Research: Predicting Diseases on Chest Radiographs Using Multimodal Data
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Korean Journal of Radiology
|
November 28, 2023
Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Chest
|
March 9, 2024
Be Careful About Metrics When Imbalanced Data Is Used for a Deep Learning Model
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori
The British Journal of Radiology
|
February 2, 2024
Letter to the editor on "Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms"
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori
Journal of Imaging Informatics in Medicine
|
June 28, 2024
Predicting EGFR Status After Radical Nephrectomy or Partial Nephrectomy for Renal Cell Carcinoma on CT Using a Self-attention-based Model: Variable Vision Transformer (vViT)
Takuma Usuzaki, Ryusei Inamori, Mami Ishikuro, et al.
Magnetic Resonance Imaging
|
May 30, 2024
Predicting isocitrate dehydrogenase status among adult patients with diffuse glioma using patient characteristics, radiomic features, and magnetic resonance imaging: Multi-modal analysis by variable vision transformer
Takuma Usuzaki, Ryusei Inamori, Takashi Shizukuishi, et al.
Journal of Imaging Informatics in Medicine
|
December 19, 2025
Transformer-based Deep Learning Models with Shape Guidance for Predicting Breast Cancer in Mammography Images
Kengo Takahashi, Yuwen Zeng, Zhang Zhang, et al.
Neuroradiology
|
March 13, 2024
Identifying key factors for predicting O6-Methylguanine-DNA methyltransferase status in adult patients with diffuse glioma: a multimodal analysis of demographics, radiomics, and MRI by variable Vision Transformer
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori, et al.
Radiological Physics and Technology
|
January 6, 2025
Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning
Keisuke Sugawara, Eichi Takaya, Ryusei Inamori, et al.
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Search research articles
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Showing results (1-10 of 16) with videos related to
Sort By:
Page
of 2
Radiology. Artificial Intelligence
|
June 12, 2024
Vision Transformer-based Deep Learning Models Accelerate Further Research for Predicting Neurosurgical Intervention
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Radiology
|
February 13, 2024
Transformer Unlocks the Gateway to Advanced Research: Predicting Diseases on Chest Radiographs Using Multimodal Data
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Korean Journal of Radiology
|
November 28, 2023
Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma
Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori
Chest
|
March 9, 2024
Be Careful About Metrics When Imbalanced Data Is Used for a Deep Learning Model
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori
The British Journal of Radiology
|
February 2, 2024
Letter to the editor on "Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms"
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori
Journal of Imaging Informatics in Medicine
|
June 28, 2024
Predicting EGFR Status After Radical Nephrectomy or Partial Nephrectomy for Renal Cell Carcinoma on CT Using a Self-attention-based Model: Variable Vision Transformer (vViT)
Takuma Usuzaki, Ryusei Inamori, Mami Ishikuro, et al.
Magnetic Resonance Imaging
|
May 30, 2024
Predicting isocitrate dehydrogenase status among adult patients with diffuse glioma using patient characteristics, radiomic features, and magnetic resonance imaging: Multi-modal analysis by variable vision transformer
Takuma Usuzaki, Ryusei Inamori, Takashi Shizukuishi, et al.
Journal of Imaging Informatics in Medicine
|
December 19, 2025
Transformer-based Deep Learning Models with Shape Guidance for Predicting Breast Cancer in Mammography Images
Kengo Takahashi, Yuwen Zeng, Zhang Zhang, et al.
Neuroradiology
|
March 13, 2024
Identifying key factors for predicting O6-Methylguanine-DNA methyltransferase status in adult patients with diffuse glioma: a multimodal analysis of demographics, radiomics, and MRI by variable Vision Transformer
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori, et al.
Radiological Physics and Technology
|
January 6, 2025
Breast cancer classification based on breast tissue structures using the Jigsaw puzzle task in self-supervised learning
Keisuke Sugawara, Eichi Takaya, Ryusei Inamori, et al.
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of 2