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3D CNN-based Deep Learning Model-based Explanatory Prognostication in Patients  with Multiple Myeloma using Whole-body MRI.
Morita K, Karashima S, Terao T, Yoshida K, Yamashita T, Yoroidaka T, Tanabe M, Imi T, Zaimoku Y, Yoshida A, Maruyama H, Iwaki N, Aoki G, Kotani T, Murata R, Miyamoto T, Machida Y, Matsue K, Nambo H, Takamatsu H. Morita K, et al. Among authors: matsue k. J Med Syst. 2024 Mar 8;48(1):30. doi: 10.1007/s10916-024-02040-8. J Med Syst. 2024. PMID: 38456950
Use of the Second Revision of the International Staging System for prognostic stratification of multiple myeloma patients in real-world clinical practice and the importance of sub-groups, including age.
Uesugi Y, Ikeda D, Fukumoto A, Tabata R, Miura D, Narita K, Takeuchi M, Matsue K. Uesugi Y, et al. Among authors: matsue k. Haematologica. 2024 May 1;109(5):1593-1597. doi: 10.3324/haematol.2023.284173. Haematologica. 2024. PMID: 38031801 Free PMC article. No abstract available.
Tumor heterogeneity and immune-evasive T follicular cell lymphoma phenotypes at single-cell resolution.
Suma S, Suehara Y, Fujisawa M, Abe Y, Hattori K, Makishima K, Sakamoto T, Sawa A, Bando H, Kaji D, Sugio T, Kato K, Akashi K, Matsue K, Carreras J, Nakamura N, Suzuki A, Suzuki Y, Ito K, Shiiba H, Chiba S, Sakata-Yanagimoto M. Suma S, et al. Among authors: matsue k. Leukemia. 2024 Feb;38(2):340-350. doi: 10.1038/s41375-023-02093-7. Epub 2023 Nov 27. Leukemia. 2024. PMID: 38012392 Free PMC article.
281 results