Zobrazeno 1 - 10
of 5 566
pro vyhledávání: '"Nakaji, So"'
Autor:
Alexeev, Yuri, Farag, Marwa H., Patti, Taylor L., Wolf, Mark E., Ares, Natalia, Aspuru-Guzik, Alán, Benjamin, Simon C., Cai, Zhenyu, Chandani, Zohim, Fedele, Federico, Harrigan, Nicholas, Kim, Jin-Sung, Kyoseva, Elica, Lietz, Justin G., Lubowe, Tom, McCaskey, Alexander, Melko, Roger G., Nakaji, Kouhei, Peruzzo, Alberto, Stanwyck, Sam, Tubman, Norm M., Wang, Hanrui, Costa, Timothy
Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extends to technical challenges within science and engineering, including th
Externí odkaz:
http://arxiv.org/abs/2411.09131
Out-of-distribution Reject Option Method for Dataset Shift Problem in Early Disease Onset Prediction
Autor:
Tosaki, Taisei, Uchino, Eiichiro, Kojima, Ryosuke, Mineharu, Yohei, Arita, Mikio, Miyai, Nobuyuki, Tamada, Yoshinori, Mikami, Tatsuya, Murashita, Koichi, Nakaji, Shigeyuki, Okuno, Yasushi
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, the prediction effectiveness is hindered by dataset shift, which involves discrepancies in data distribution between the training
Externí odkaz:
http://arxiv.org/abs/2405.19864
Autor:
Guo, Naixu, Yu, Zhan, Choi, Matthew, Agrawal, Aman, Nakaji, Kouhei, Aspuru-Guzik, Alán, Rebentrost, Patrick
Generative machine learning methods such as large-language models are revolutionizing the creation of text and images. While these models are powerful they also harness a large amount of computational resources. The transformer is a key component in
Externí odkaz:
http://arxiv.org/abs/2402.16714
Autor:
Wang, Lujia, Wang, Hairong, D'Angelo, Fulvio, Curtin, Lee, Sereduk, Christopher P., De Leon, Gustavo, Singleton, Kyle W., Urcuyo, Javier, Hawkins-Daarud, Andrea, Jackson, Pamela R., Krishna, Chandan, Zimmerman, Richard S., Patra, Devi P., Bendok, Bernard R., Smith, Kris A., Nakaji, Peter, Donev, Kliment, Baxter, Leslie C., Mrugała, Maciej M., Ceccarelli, Michele, Iavarone, Antonio, Swanson, Kristin R., Tran, Nhan L., Hu, Leland S., Li, Jing
Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learnin
Externí odkaz:
http://arxiv.org/abs/2401.00128
Autor:
Yoshihiko Furuta, Masato Akiyama, Naoki Hirabayashi, Takanori Honda, Mao Shibata, Tomoyuki Ohara, Jun Hata, Chikashi Terao, Yukihide Momozawa, Yasuko Tatewaki, Yasuyuki Taki, Shigeyuki Nakaji, Tetsuya Maeda, Kenjiro Ono, Masaru Mimura, Kenji Nakashima, Jun-ichi Iga, Minoru Takebayashi, Toshiharu Ninomiya, On behalf of the Japan Prospective Studies for Aging and Dementia (JPSC-AD) Study Group
Publikováno v:
npj Genomic Medicine, Vol 9, Iss 1, Pp 1-9 (2024)
Abstract The genetic architecture of white matter lesions (WMLs) in Asian populations has not been well-characterized. Here, we performed a genome-wide association study (GWAS) to identify loci associated with the WML volume. Brain MRI and DNA sample
Externí odkaz:
https://doaj.org/article/d640617a2b1b4389bb2d2d33f3d491f0
Autor:
Tadashi Miyazaki, Naoki Ozato, Tohru Yamaguchi, Yoko Sugiura, Hiromitsu Kawada, Yoshihisa Katsuragi, Noriko Osaki, Tatsuya Mikami, Ken Ito, Koichi Murashita, Shigeyuki Nakaji, Yoshinori Tamada
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract The association between visceral fat area (VFA) and locomotive syndrome (LS) has been extensively studied in the older population; however, the association between VFA and early-stage LS (stage 1 [LS1]) remains unclear. In this cross-section
Externí odkaz:
https://doaj.org/article/f83717da9cc44806a6470635c85e9f56
Partial differential equations (PDEs) are ubiquitous in science and engineering. Prior quantum algorithms for solving the system of linear algebraic equations obtained from discretizing a PDE have a computational complexity that scales at least linea
Externí odkaz:
http://arxiv.org/abs/2306.11802
Estimation of the expectation value of observables is a key subroutine in quantum computing and is also the bottleneck of the performance of many near-term quantum algorithms. Many works have been proposed to reduce the number of measurements needed
Externí odkaz:
http://arxiv.org/abs/2305.02439
Publikováno v:
Quantum Mach. Intell. 6, 14 (2024)
Quantum machine learning with variational quantum algorithms (VQA) has been actively investigated as a practical algorithm in the noisy intermediate-scale quantum (NISQ) era. Recent researches reveal that the data reuploading, which repeatedly encode
Externí odkaz:
http://arxiv.org/abs/2305.00688
Publikováno v:
PRX Quantum 5, 020330 (2024)
Hamiltonian simulation is known to be one of the fundamental building blocks of a variety of quantum algorithms such as its most immediate application, that of simulating many-body systems to extract their physical properties. In this work, we presen
Externí odkaz:
http://arxiv.org/abs/2302.14811