【査読付き英文論文】

*1. Hamamoto R: Application of Artificial Intelligence for Medical Research. Biomolecules, 11, 90 (2021) [pubmed]

*2. Komatsu M, Sakai A, Komatsu R, Matsuoka R, Yasutomi S, Shozu K, Dozen A, Machino H, Hidaka H, Arakaki T, Asada K, Kaneko S, Sekizawa A, Hamamoto R: Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning. Applied Sciences, 11, 371 (2021) [link]

*3. Yasutomi S, Arakaki T, Matsuoka R, Sakai A, Komatsu R, Shozu K, Dozen A, Machino H, Asada K, Kaneko S, Dozen A, Machino H, Asada K, Kaneko S, Sekizawa A, Hamamoto R, Komatsu M: Shadow Estimation for Ultrasound Images Using Auto-Encoding Structures and Synthetic Shadows. Applied Sciences, 11, 1127 (2021) [link]

*4. Kobayashi K, Hamamoto R, Itami J: Tensor regression-based model to investigate heterogeneous spatial radiosensitivity after I-125 seed implantation for prostate cancer. In Vivo, 35, 489-497 (2021) [pubmed]

*5. Ozawa T, Kaneko S, Szulzewsky F, Qiao Z, Takadera M, Narita Y, Kondo T, Holland EC, Hamamot R, Ichimura K: C11orf95-RELA fusion drives aberrant gene expression through the unique epigenetic regulation for ependymoma formation. Acta Neuropathologica Communications, 9, 36 (2021) [pubmed]

*6. Takayanagi D, Hirose S, Kuno I, Asami Y, Murakami N, Matsuda M, Shimada Y, Sunami K, Komatsu M, Hamamoto R, Kobayashi-Kato M, Matsumoto K, Kohno T, Kato T, Shiraishi K, Yoshida H: Comparative Analysis of Genetic Alterations, HPV-Status, and PD-L1 Expression in Neuroendocrine Carcinomas of the Cervix. Cancers (Basel), 13, 1215 (2021) [pubmed]

*7. Takahashi S, Takahashi M, Kinoshita M, Miyake M, Kawaguchi R, Shinojima N, Mukasa A, Saito K, Nagane M, Otani R, Higuchi F, Tanaka S, Hata N, Tamura K, Tateishi K, Nishikawa R, Arita H, Nonaka M, Uda T, Fukai J, Okita Y, Tsuyuguchi N, Kanemura Y, Kobayashi K, Sese J, Ichimura k, Narita Y, Hamamoto R: Fine-Tuning Approach for Segmentation of Gliomas in Brain Magnetic Resonance Images with a Machine Learning Method to Normalize Image Differences among Facilities. Cancers (Basel), 13, 1415 (2021) [pubmed]

*8. Takahashi S, Takahashi M, Tanaka S, Takayanagi S, Takami H, Yamazawa E, Nambu S, Miyake M, Satomi K, Ichimura K, Narita Y, Hamamoto R: A New Era of Neuro-Oncology Research Pioneered by Multi-Omics Analysis and Machine Learning. Biomolecules, 11, 565 (2021) [pubmed]

*9. Kaneko S, Mitsuyama T, Shiraishi K, Ikawa N, Shozu K, Dozen A, Machino H, Asada K, Komatsu M, Kukita A, Sone K, Yoshida H, Motoi N, Hayami S, Yoneoka Y, Kato T, Kohno T, Natsume T, Keudell GV, Saloura V, Yamaue H, Hamamoto R: Genome-Wide Chromatin Analysis of FFPE Tissues Using a Dual-Arm Robot with Clinical Potential. Cancers (Basel), 13, 2126 (2021) [pubmed]

*10. Asada K, Kaneko S, Takasawa K, Machino H, Takahashi S, Shinkai N, Shimoyama R, Komatstu M, Hamamoto R: Integrated Analysis of Whole Genome and Epigenome Data Using Machine Learning Technology: Toward the Establishment of Precision Oncology. Front Oncol,13, 666397 (2021) [pubmed]

*11. Kobayashi K, Miyake M, Takahashi M, Hamamoto R: Observing Deep Radiomics for the Classification of Glioma Grades. Sci Rep,11, 10942 (2021) [pubmed]

*12. Komatsu M, Sakai A, Dozen A, Shozu A, Yasutomi S, Machino H, Asada K, Kaneko S, Hamamoto R: Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging. Biomedicines,9, 720 (2021) [pubmed]

*13. Yamada M, Saito Y, Yamada S, Kondo H, Hamamoto R: Detection of flat colorectal neoplasia by artificial intelligence: A systematic review. Best Pract Res Clin Gastroenterol, 52-53, 101745 (2021) [pubmed]

*14. Kawaguchi RK, Takahashi M, Miyake M, Kinoshita M, Takahashi S, Ichimura K, Hamamoto R, Narita Y, Sese J: Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals. Cancers (Basel), 13, 3611 (2021) [pubmed]

*15. Kobayashi K, Hataya R, Kurose Y, Miyake M, Takahashi M, Nakagawa A, Harada T, Hamamoto R: Decomposing normal and abnormal features of medical images for content-based image retrieval of glioma imaging. Med Image Anal, 8;74:102227 (2021) [pubmed]

*16. Kaneko S, Takasawa K, Asada K, Shinkai N, Bolatkan A, Yamada M, Takahashi S, Machino H, Kobayashi K, Komatsu M, Hamamoto R: Epigenetic Mechanisms Underlying COVID-19 Pathogenesis. Biomedicines, 9, 1142 (2021) [pubmed]

*17. Asada K, Komatsu M, Shimoyama R, Takasawa K, Shinkai N, Sakai A, Bolatkan A, Yamada M, Takahashi S, Machino H, Kobayashi K, Kaneko S, Hamamoto R: Application of Artificial Intelligence in COVID-19 Diagnosis and Therapeutics. J Pers Med, 11, 886 (2021) [pubmed]

*18. Kuno I, Takayanagi D, Asami Y, Murakami N, Matsuda M, Shimada Y, Hirose S, Kato MK, Komatsu M, Hamamoto R, Okuma K, Kohno T, Itami J, Yoshida H, Shiraishi K, Kato T: TP53 mutants and non-HPV16/18 genotypes are poor prognostic factors for concurrent chemoradiotherapy in locally advanced cervical cancer. Sci Rep, 11, 19261 (2021) [pubmed]

*19. Asada K, Takasawa K, Machino H, Takahashi S, Shinkai N, Bolatkan A, Kobayashi K, Komatsu M, Kaneko S, Okamoto K, Hamamoto R: Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research. Biomedicines, 9, 1513 (2021) [pubmed]

*20. Lee K, Kim K, Ryu TY, Jung CR, Lee MS, Lim JH, Park K, Kim DS, Son MY, Hamamoto R, Cho HS: EHMT1 knockdown induces apoptosis and cell cycle arrest in lung cancer cells by increasing CDKN1A expression. Mol Oncol, 15, 2989-3002 (2021) [pubmed]