Impact of Downsampling Size and Interpretation Methods on Diagnostic Accuracy in Deep Learning Model for Breast Cancer Using Digital Breast Tomosynthesis Images von Inamori, Ryusei, Kaneno, Tomofumi, Oba, Ken, Takaya, Eichi, Hirahara, Daisuke, Kobayashi, Tomoya, Kawaguchi, Kurara, Adachi, Maki, Shimokawa, Daiki, Takahashi, Kengo, Tsunoda, Hiroko, Ueda, Takuya

Volltext

Be Careful About Metrics When Imbalanced Data Is Used for a Deep Learning Model von Usuzaki, Takuma, Takahashi, Kengo, Inamori, Ryusei

Volltext

Letter to the editor on "Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms" von Usuzaki, Takuma, Takahashi, Kengo, Inamori, Ryusei

Volltext

Identifying key factors for predicting O6-Methylguanine-DNA methyltransferase status in adult patients with diffuse glioma: a multimodal analysis of demographics, radiomics, and MR... von Usuzaki, Takuma, Takahashi, Kengo, Inamori, Ryusei, Morishita, Yohei, Shizukuishi, Takashi, Takagi, Hidenobu, Ishikuro, Mami, Obara, Taku, Takase, Kei

Volltext

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) von Usuzaki, Takuma, Inamori, Ryusei, Ishikuro, Mami, Obara, Taku, Takaya, Eichi, Homma, Noriyasu, Takase, Kei

Volltext

Grading diffuse glioma based on 2021 WHO grade using self-attention-base deep learning architecture: variable Vision Transformer (vViT) von Usuzaki, Takuma, Takahashi, Kengo, Inamori, Ryusei, Morishita, Yohei, Takagi, Hidenobu, Shizukuishi, Takashi, Toyama, Yoshitaka, Abe, Mirei, Ishikuro, Mami, Obara, Taku, Majima, Kazuhiro, Takase, Kei

Volltext

Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma von Kengo Takahashi, Takuma Usuzaki, Ryusei Inamori

Volltext

医用画像解析のためのマルチタスク表現学習 von 髙屋, 英知, 稲森, 瑠星

Volltext