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R. Takahashi, A. Tanaka, T. Saito, S. Ohashi, M. Muto, and M. Yamaguchi
Organ-On-A-Chip Platforms Created Through Buckled Microchannels of Porous Hydrogel Films
Adv. Mater. Technol. (2024).
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S. Himori, R. Takahashi, A. Tanaka, and M. Yamaguchi
Direct Metal Transfer on Swellable Hydrogel with Dehydration-Induced Physical Adhesion
ACS Omega 9 (41) 42261-42266 (2024).
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K. Sumitomo, H. Yoshimizu, A. Oshima, M. Yamaguchi, and A. Heya
Interactions between supported lipid bilayers and substrates that affect lateral diffusion of lipids
Jpn. J. Appl. Phys. 63 (9), 09SP24 (2024).
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A. Yamamoto, Y. Sakamaki, W. Abuillan, O. Konovalov, Y. Ueno, and M. Tanaka
Structural and Mechanical Characterization of DNA-Tethered Membranes on Graphene
Langmuir (2024).
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E. Nakahara, T. Iidaka, A. Chiba, H. Kurasawa, A. Fujino, N. Shiomi, H. Maruyama, C. Horii, S. Muraki, H. Oka, H. Kawaguchi, K. Nakamura, T. Akune, S. Tanaka, and N. Yoshimura
Identifying factors associated with locomotive syndrome using machine learning methods: The third survey of the research on osteoarthritis/osteoporosis against disability study
Geriatr. Gerontol. Int. (2024).
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K. Fujiyoshi, M. Yamaoka-Tojo, K. Fujiyoshi, T. Komatsu, J. Oikawa, K. Kashino, H. Tomoike, and J. Ako
Beat-to-beat alterations of acoustic intensity and frequency at the maximum power of heart sounds are associated with NT-proBNP levels
Front. Cardiovasc. Med. 11, 1372543 (2024).
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R. Nishikimi, M. Nakano, K. Kashino, and S. Tsukada
Variational autoencoder-based neural electrocardiogram synthesis trained by FEM-based heart simulator
Cardiovasc. Digit. Health J. 5 (1) 19-28 (2024).
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T. Ogasawara, M. Mukaino, K. Matsunaga, Y. Wada, T. Suzuki, Y. Aoshima, S. Furuzawa, Y. Kono, E. Saitoh, M. Yamaguchi, Y. Otaka, and S. Tsukada
Prediction of stroke patients' bedroom-stay duration: machine-learning approach using wearable sensor data
Front. Bioeng. Biotechnol. 11, 1285945 (2024).
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H. Kurasawa, K. Waki, T. Seki, A. Chiba, A. Fujino, K. Hayashi, E. Nakahara, T. Haga, T. Noguchi, and K. Ohe
Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development
JMIR AI 3, e56700 (2024).
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E. Mizuno, T. Ogasawara, M. Mukaino, M. Yamaguchi, S. Tsukada, S. Sonoda, and Y. Otaka
Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study
JMIR Form. Res. 8, e51546 (2024).
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Y. Kono, M. Mukaino, Y. Ozawa, K. Mizutani, Y. Senju, T. Ogasawara, M. Yamaguchi, T. Muramatsu, H. Izawa, and Y. Otaka
Clinical impact of non-lying time on hospital-associated functional decline in older patients undergoing transcatheter aortic valve implantation
Heart Vessels 39 (3) 266-272 (2024).