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9篇 您的检索式:作者名="YAMADA GEN"
    题名 作者 年代 出处 被引量
1Narrow band imaging yields clear images of subepithelial microvessels in large airways in combination with high magnification bronchovideoscopy显示文摘Gen Yamada Noriharu Shijubo Junya Kitada 2007J Bronchol2007,14,:1
2The regulation of endogenous retinoic acid level through CYP26B1 is required for elevation of palatal shelves显示文摘Junko Okano Wataru Kimura Virginia E. Papaionnou Naoyuki Miura Gen Yamada Kohei Shiota Yasuo Sakai 2012Dev Dyn2012,,11:1
3Multivariate Analysis of Genetic and Acquired Factors; T235 Variant of the Angiotensinogen Gene Is a Potent Independent Risk Factor for Preeclampsia显示文摘Gen Kobashi Koichi Shido Akira Hata Hideto Yamada Emi-Hirayama Kato Masao Kanamori Seiichiro Fujimoto Kiyotaro Kondo 2001Semin Thromb Hemost2001,,02:1
4Requirement of CD9 on the Egg Plasma Membrane for Fertilization显示文摘Kenji Miyado Gen Yamada Shuichi Yamada 2000Science2000,287,:1
5Centrilobular Nodules Correlate With Air Trapping in Diffuse Panbronchiolitis During Erythromycin Therapy显示文摘Gen Yamada Tomofumi Igarashi Eiji Itoh 2001Chest2001,120,1:1
6Adenoviral Oncolytic Suicide Gene Therapy for a Peritoneal Dissemination Model of Gastric Cancer in Mice显示文摘Yu Imamura Shinji Ishikawa Nobutaka Sato Ryuichi Karashima Kotaro Hirashima Yukiharu Hiyoshi Youhei Nagai Yoshikatsu Koga Naoko Hayashi Masayuki Watanabe Gen Yamada Hideo Baba 2010Annals of Surgical Oncology2010,,2:1
7Vibration analysis of disk beam coupled System having cyclically symmetric structure显示文摘YAMADA GEN KOBASH YUKINORI 1994Transactions of the Japan Society of Mechanical Engineers1994,60,515:1
8Long Noncoding RNA NEAT1-Dependent SFPQ Relocation from Promoter Region to Paraspeckle Mediates IL8 Expression upon Immune Stimuli显示文摘Katsutoshi Imamura Naoto Imamachi Gen Akizuki Michiko Kumakura Atsushi Kawaguchi Kyosuke Nagata Akihisa Kato Yasushi Kawaguchi Hiroki Sato Misako Yoneda Chieko Kai Tetsushi Yada Yutaka Suzuki Toshimichi Yamada Takeaki Ozawa Kiyomi Kaneki Tsuyoshi Inoue Mi 2014Molecular Cell2014,,3:1
9Predictive model of risk factors of High Flow Nasal Cannula using machine learning in COVID-19显示文摘With the rapid increase in the number of COVID-19 patients in Japan,the number of patients receiving oxygen at home has also increased rapidly,and some of these patients have died.An efficient approach to identify high-risk patients with slowly progressing and rapidly worsening COVID-19,and to avoid missing the timing of therapeutic intervention will improve patient prognosis and prevent medical complications.Patients admitted to medical institutions in Japan from November 14,2020 to April 11,2021 and registered in the COVID-19 Registry Japan were included.Risk factors for patients with High Flow Nasal Cannula invasive respiratory management or higher were comprehensively explored using machine learning.Age-specific cohorts were created,and severity prediction was performed for the patient surge period.We were able to obtain a model that was able to predict severe disease with a sensitivity of 57%when the specificity was set at 90%for those aged 40e59 years,and with a specificity of 50%and 43%when the sensitivity was set at 90%for those aged 60e79 years and 80 years and older,respectively.We were able to identify lactate dehydrogenase level(LDH)as an important factor in predicting the severity of illness in all age groups.Using machine learning,we were able to identify risk factors with high accuracy,and predict the severity of the disease.We plan to develop a tool that will be useful in determining the indications for hospitalisation for patients undergoing home care and early hospitalisation.Nobuaki Matsunaga Keisuke Kamata Yusuke Asai Shinya Tsuzuki Yasuaki Sakamoto Shinpei Ijichi Takayuki Akiyama a Jiefu Yu Gen Yamada Mari Terada Setsuko Suzuki Kumiko Suzuki Sho Saito Kayoko Hayakawa Norio Ohmagari 2022Infectious Disease Modelling2022,7,3:0
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