2019 - 2023 Computer-aided and automatic diagnosis of chest x-ray images using deep learning
2019 - 2022 Basic research on the construction of a database of diversity lung nodules and the development of a self-learning diagnostic imaging support system
2016 - 2019 Development of computer-aided diagnosis system for lung cancer CT screening using deep learning
2018 - 2019 敵対性生成ネットワークによる胸部単純 X 線写真の擬似病変の生成
2014 - 2017 MR Hemodynamic Evaluations of Hepatic Vasculatures
2015 - 2016 深層学習を用いた超低線量CTのノイズ除去とその臨床応用
2014 - 2015 超低線量CTの臨床応用について
2013 - Emphysema Quantification on Low-Dose CT by Percentage of Low-Attenuation Volume and Size Distribution Analysis of Low-Attenuation Clusters: Effect of Adaptive Iterative Dose Reduction using 3D Processing
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Papers (133)：
Yasuhisa Kurata, Mizuho Nishio, Yusaku Moribata, Satoshi Otani, Yuki Himoto, Satoru Takahashi, Jiro Kusakabe, Ryota Okura, Marina Shimizu, Keisuke Hidaka, et al. Development of deep learning model for diagnosing muscle-invasive bladder cancer on MRI with vision transformer. Heliyon. 2024. 10. 16. e36144
Aki Miyazaki, Mizuho Nishio, Atsushi Fujita, Masaaki Kohta, Yasuyuki Kojita, Shintaro Horii, Takashi Sasayama, Takamichi Murakami. Predicting the O'Kelly-Marotta scale score after flow-diverter stent placement using silent MRA. Japanese journal of radiology. 2024
Yuki Himoto, Mizuho Nishio, Koji Yamanoi, Yuka Kuriyama Matsumoto. Reply to Letter to the Editor: Nodal infiltration in endometrial cancer: a prediction model using best subset regression. European radiology. 2024
Mizuki Tagami, Mizuho Nishio, Atsuko Yoshikawa, Norihiko Misawa, Atsushi Sakai, Yusuke Haruna, Mami Tomita, Atsushi Azumi, Shigeru Honda. Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images. Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie. 2024
Takaaki Matsunaga, Atsushi Kono, Mizuho Nishio, Takahiro Yoshii, Hidetoshi Matsuo, Mai Takahashi, Takuya Takahashi, Yu Taniguchi, Hidekazu Tanaka, Kenichi Hirata, et al. Development and web deployment of prediction model for pulmonary arterial pressure in chronic thromboembolic pulmonary hypertension using machine learning. PloS one. 2024. 19. 4. e0300716
2024/01 - 現在 BMC Medical Informatics and Decision Making Senior Editorial Board Member
2022/08 - 現在 Frontiers in Nuclear Medicine Associate Editor
2021/08 - 現在 Cancers Lead Guest Editor, Special Issue "Multi-Modality Imaging and Multi-Omics Approach of Cancers With Machine Learning/Deep Learning"
2020/11 - 現在 International Journal of Imaging Systems and Technology EDITORIAL BOARD MEMBER
2020/09 - 2023/12 BMC Medical Informatics and Decision Making EDITORIAL BOARD MEMBER
2021/11 - 2022/08 Frontiers in Nuclear Medicine Review Editor
2021/01 - 2022/04 Frontiers in Artificial Intelligence Lead Guest Editor, Research Topic "Automatic Lung Nodule Detection with Deep Learning"
2020/02 - 2021/04 Applied Science Lead Guest Editor, Special Issue "Machine Learning/Deep Learning in Medical Image Processing"
2019/06 - 2020/11 Heliyon Editorial Advisory Board Member
2019/04 - 2019/05 Heliyon Editorial Board Member
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Awards (5)：
2023/05 - The 50 most cited articles on artificial intelligence for lung cancer imaging Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning
2022/04 - Annals of Nuclear Medicine 2021 Frequently Cited Papers Usefulness of gradient tree boosting for predicting histological subtype and EGFR mutation status of non-small cell lung cancer on F-18 FDG-PET/CT.
2021/02 - Translational Lung Cancer Research Reviewer of the Month (February, 2021)
2019/12 - PLOS ONE. The top 10% most cited PLOS ONE authors of 2018 Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning
2019/03 - Insights into Imaging Most Downloaded Paper Award 2018 Convolutional neural networks: an overview and application in radiology
