Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ryusuke Sato"'
Autor:
Yukihiko Iizuka, Takahiko Saida, Kazumasa Yokoyama, Masakazu Hase, Shinichi Torii, Haruki Makioka, Ryusuke Sato, Yan Ling
Publikováno v:
Neurology and Therapy
Introduction Natalizumab, a humanized anti-α4 integrin monoclonal antibody, received marketing approval in Japan in 2014 for the treatment of multiple sclerosis (MS). Because the previous large-scale clinical trials of natalizumab were mainly conduc
Autor:
Masanori Takuma, Tomohiro Sato, Maui Iwamoto, Yoshimasa Takahashi, Ken-ichi Saitoh, Ryusuke Sato
Publikováno v:
The Proceedings of Mechanical Engineering Congress, Japan. 2020:J01220
Autor:
Kumiko Miyazaki, Ryusuke Sato
Publikováno v:
2018 Portland International Conference on Management of Engineering and Technology (PICMET).
Although AI was proposed by J. McCarthy back in 1956, 60 years later, we are beginning to witness a surge of interest in the practical applications of AI in many sectors. However, the actual adoption rate of AI in businesses has been quite low. The c
Autor:
Atsushi Sato, Yoshiyuki Hoshi, Ryusuke Sato, Ayami Isonishi, Masue Imaizumi, Yoshihiro Fujimura, Masaei Onuma, Masanori Matsumoto, Yukiko Tsunematsu
Publikováno v:
Pediatric Hematology and Oncology. 27:53-58
Although acquired idiopathic thrombotic thrombocytopenic purpura (ai-TTP) is rare in children, the authors present the case of a 9-month-old boy with ai-TTP showing severe deficiency of ADAMTS13 activity by its inhibitory IgG-autoantibody (4.8 Bethes
Autor:
Minako Ono, Tomoyuki Miyamoto, Tetsuharu Nagamoto, Kataharu Sumi, Yoshinori Murashima, Ryusuke Sato, Ari Iwaoka, Yoko Santo, Yoko Mouri, Takeshi Mouri
Publikováno v:
Circulation. 131
Objective: This retrospective analysis aimed to identify the risk factors of Kawasaki disease (KD) resistant to second intravenous immunoglobulin ( IVIG) and design the score system discerning IVIG resistant patients in acute phase. Materials and Met
Publikováno v:
IJCNN
In this paper, we propose a Three Ensemble neural network rule extraction algorithm. Then we investigate Hayashi's first question, “Can the Ensemble-Recursive-Rule eXtraction (E-Re-RX) algorithm be extended to an ensemble neural network consisting