Impact of Downsampling Size and Interpretation Methods on Diagnostic Accuracy in Deep Learning Model for Breast Cancer Using Digital Breast Tomosynthesis Images. The Tohoku Journal of Experimental Medicine. 11 July 2024. https://doi.org/10.1620/tjem.2024.J071
共著
Grading diffuse glioma based on 2021 WHO grade using self-attention-base deep learning architecture: variable Vision Transformer (vViT). Biomedical Signal Processing and Control. 29 Jan 2024. https://doi.org/10.1016/j.bspc.2024.106001
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. Neuroradiology. 12 Mar 2024. https://doi.org/10.1007/s00234-024-03329-8
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. Magnetic Resonance Imaging. 22 May 2024. https://doi.org/10.1016/j.mri.2024.05.012
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). Journal of Imaging Informatics in Medicine. 28 June 2024. https://doi.org/10.1007/s10278-024-01180-0
学会
医用画像を用いた深層学習 Data AugmentationにおけるSuperMixの有効性の検証. 第6回日本メディカルAI学会学術集会. ポスター発表. 2024年6月21日.
