Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Eichi Takaya"'
Autor:
Saori Ikumi, Takuya Shiga, Takuya Ueda, Eichi Takaya, Yudai Iwasaki, Yu Kaiho, Kunio Tarasawa, Kiyohide Fushimi, Yukiko Ito, Kenji Fujimori, Masanori Yamauchi
Publikováno v:
Journal of Intensive Care, Vol 11, Iss 1, Pp 1-11 (2023)
Abstract Background Japan has four types of intensive care units (ICUs) that are divided into two categories according to the management fee charged per day: ICU management fees 1 and 2 (ICU1/2) (equivalent to high-intensity staffing) and 3 and 4 (IC
Externí odkaz:
https://doaj.org/article/4300785afa884aa0829c724d495bd923
Autor:
Kenji Nakano, Kotaro Nochioka, Satoshi Yasuda, Daito Tamori, Takashi Shiroto, Yudai Sato, Eichi Takaya, Satoshi Miyata, Eiryo Kawakami, Tetsuo Ishikawa, Takuya Ueda, Hiroaki Shimokawa
Publikováno v:
ESC Heart Failure, Vol 10, Iss 3, Pp 1597-1604 (2023)
Abstract Aims Current approaches to classify chronic heart failure (HF) subpopulations may be limited due to the diversity of pathophysiology and co‐morbidities in chronic HF. We aimed to elucidate the clusters of chronic patients with HF by data
Externí odkaz:
https://doaj.org/article/dc22020d47644ba383f2dc5e0c81f81c
Autor:
Shinya Sonobe, Tetsuo Ishikawa, Kuniyasu Niizuma, Eiryo Kawakami, Takuya Ueda, Eichi Takaya, Carlos Makoto Miyauchi, Junya Iwazaki, Ryuzaburo Kochi, Toshiki Endo, Arun Shastry, Vijayananda Jagannatha, Ajay Seth, Atsuhiro Nakagawa, Masahiro Yoshida, Teiji Tominaga
Publikováno v:
Interdisciplinary Neurosurgery, Vol 29, Iss , Pp 101560- (2022)
Objective: Predicting outcomes after intracerebral hemorrhage (ICH) may help improve patient outcomes. We developed and validated a machine learning prediction model for post-rehabilitation functional outcomes after ICH. Patient selection and explana
Externí odkaz:
https://doaj.org/article/2d5fac8fdf4341ea8c48b8b6a7bd9274
Publikováno v:
PeerJ Computer Science, Vol 6, p e312 (2020)
Background Deep learning using convolutional neural networks (CNN) has achieved significant results in various fields that use images. Deep learning can automatically extract features from data, and CNN extracts image features by convolution processi
Externí odkaz:
https://doaj.org/article/15402d9be32648cfa1e8df7729cff223
Autor:
Yusuke Takeichi, Tatsuya Uebi, Naoyuki Miyazaki, Kazuyoshi Murata, Kouji Yasuyama, Kanako Inoue, Toshinobu Suzaki, Hideo Kubo, Naoko Kajimura, Jo Takano, Toshiaki Omori, Ryoichi Yoshimura, Yasuhisa Endo, Masaru K. Hojo, Eichi Takaya, Satoshi Kurihara, Kenta Tatsuta, Koichi Ozaki, Mamiko Ozaki
Publikováno v:
Frontiers in Cellular Neuroscience, Vol 12 (2018)
Ants are known to use a colony-specific blend of cuticular hydrocarbons (CHCs) as a pheromone to discriminate between nestmates and non-nestmates and the CHCs were sensed in the basiconic type of antennal sensilla (S. basiconica). To investigate the
Externí odkaz:
https://doaj.org/article/ddb48e9bc76240e3926dee487e036310
Autor:
Takafumi Haraguchi, Yasuyuki Kobayashi, Daisuke Hirahara, Tatsuaki Kobayashi, Eichi Takaya, Mariko Takishita Nagai, Hayato Tomita, Jun Okamoto, Yoshihide Kanemaki, Koichiro Tsugawa
Publikováno v:
Journal of X-Ray Science and Technology. 31:627-640
BACKGROUND: In breast cancer diagnosis and treatment, non-invasive prediction of axillary lymph node (ALN) metastasis can help avoid complications related to sentinel lymph node biopsy. OBJECTIVE: This study aims to develop and evaluate machine learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad7a98afca7691c00a1353877030c96e
https://doi.org/10.3233/xst-230009
https://doi.org/10.3233/xst-230009
Autor:
Kohei Isemoto, Yuma Waseda, Motohiro Fujiwara, Koichiro Kimura, Daisuke Hirahara, Tatsunori Saho, Eichi Takaya, Shohei Fukuda, Hajime Tanaka, Soichiro Yoshida, Minato Yokoyama, Yasuhisa Fujii
Publikováno v:
Journal of Urology. 209
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbd8747981d4939b98f7bb6c78452292
https://doi.org/10.1097/ju.0000000000003295.04
https://doi.org/10.1097/ju.0000000000003295.04
Autor:
Hayato Tomita, Tatsuaki Kobayashi, Eichi Takaya, Sono Mishiro, Daisuke Hirahara, Atsuko Fujikawa, Yoshiko Kurihara, Hidefumi Mimura, Yasuyuki Kobayashi
Publikováno v:
European Radiology. 32:5353-5361
This preliminary study aimed to develop a deep learning (DL) model using diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps to predict local recurrence and 2-year progression-free survival (PFS) in laryngeal and hypopharyn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe054751119e017356604c008555e902
https://doi.org/10.1007/s00330-022-08630-9
https://doi.org/10.1007/s00330-022-08630-9
Publikováno v:
Journal of St. Marianna University. 13:95-100
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68f8bfe2a136f31a1f0efcb578a7a51e
https://doi.org/10.17264/stmarieng.13.95
https://doi.org/10.17264/stmarieng.13.95
Autor:
Daiki Shimokawa, Kengo Takahashi, Ken Oba, Eichi Takaya, Takuma Usuzaki, Mizuki Kadowaki, Kurara Kawaguchi, Maki Adachi, Tomofumi Kaneno, Toshinori Fukuda, Kazuyo Yagishita, Hiroko Tsunoda, Takuya Ueda
Purpose:To develop a deep learning (DL)-based algorithm to predict the presence of stromal invasion of breast cancer on digital breast tomosynthesis (DBT).Materials and Methods:The institutional review board approved this retrospective study and waiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::289b039185ef58e177ecf0c040b000dd
https://doi.org/10.21203/rs.3.rs-1807556/v1
https://doi.org/10.21203/rs.3.rs-1807556/v1
