Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Yasukuni Mori"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Abstract To ensure the safety of railroad operations, it is important to monitor and forecast track geometry irregularities. A higher safety requires forecasting with higher spatiotemporal frequencies, which in turn requires capturing spatial correla
Externí odkaz:
https://doaj.org/article/ce066ca5df2c447ea300670d277606fe
Autor:
Yasukuni Mori, Hajime Yokota, Isamu Hoshino, Yosuke Iwatate, Kohei Wakamatsu, Takashi Uno, Hiroki Suyari
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional
Externí odkaz:
https://doaj.org/article/28bc13331950486aa5c2931065e08487
Autor:
Yosuke Iwatate, Hajime Yokota, Isamu Hoshino, Fumitaka Ishige, Naoki Kuwayama, Makiko Itami, Yasukuni Mori, Satoshi Chiba, Hidehito Arimitsu, Hiroo Yanagibashi, Wataru Takayama, Takashi Uno, Jason Lin, Yuki Nakamura, Yasutoshi Tatsumi, Osamu Shimozato, Hiroki Nagase
Publikováno v:
PLoS ONE, Vol 17, Iss 6 (2022)
Transcriptomic analysis of cancer samples helps identify the mechanism and molecular markers of cancer. However, transcriptomic analyses of pancreatic cancer from the Japanese population are lacking. Hence, in this study, we performed RNA sequencing
Externí odkaz:
https://doaj.org/article/531c38c3c0214a17b9031bed43148906
Autor:
Yuki Terasaki, Hajime Yokota, Kohei Tashiro, Takuma Maejima, Takashi Takeuchi, Ryuna Kurosawa, Shoma Yamauchi, Akiyo Takada, Hiroki Mukai, Kenji Ohira, Joji Ota, Takuro Horikoshi, Yasukuni Mori, Takashi Uno, Hiroki Suyari
Publikováno v:
Frontiers in Neurology, Vol 12 (2022)
Current deep learning-based cerebral aneurysm detection demonstrates high sensitivity, but produces numerous false-positives (FPs), which hampers clinical application of automated detection systems for time-of-flight magnetic resonance angiography. T
Externí odkaz:
https://doaj.org/article/f5926aeb26784ec78c044131d99b930c
Autor:
Toshio Kumakiri, Shinichiro Mori, Yasukuni Mori, Ryusuke Hirai, Ayato Hashimoto, Yasuhiko Tachibana, Hiroki Suyari, Hitoshi Ishikawa
Publikováno v:
Physical and Engineering Sciences in Medicine. 46:659-668
Publikováno v:
Oncology Letters; Nov2023, Vol. 26 Issue 5, p1-10, 10p
Autor:
Yosuke Iwatate, Yuki Nakamura, Hiroki Nagase, Yasutoshi Tatsumi, Isamu Hoshino, Makiko Itami, Hajime Yokota, Osamu Shimozato, Naoki Kuwayama, Yasukuni Mori, Fumitaka Ishige, Takashi Uno
Publikováno v:
Cancer Science
Tumor mutational burden (TMB) is gaining attention as a biomarker for responses to immune checkpoint inhibitors in cancer patients. In this study, we evaluated the status of TMB in primary and liver metastatic lesions in patients with colorectal canc
Autor:
Toshio Kumakiri, Shinichiro Mori, Yasukuni Mori, Ryusuke Hirai, Ayato Hashimoto, Yasuhiko Tachibana, Hiroki suyari, Hitoshi Ishikawa
Since particle beam distribution is vulnerable to change in bowel gas because of its low density, we developed a deep neural network (DNN) for bowel gas segmentation on X-ray images. We used 6688 image datasets from 209 cases as training data and 102
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a3132a3b809a3ed9fb8f0a8e3b52a49
https://doi.org/10.21203/rs.3.rs-2269635/v1
https://doi.org/10.21203/rs.3.rs-2269635/v1
To ensure the safety of railroad operations, it is important to monitor and forecast track geometry irregularities. A higher safety requires forecasting with higher spatiotemporal frequencies, which in turn requires capturing spatial correlations. Ad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::269d09bc5f8ed4be9ca2a78ff4782458
http://arxiv.org/abs/2211.03549
http://arxiv.org/abs/2211.03549
Autor:
Yosuke Iwatate, Takashi Uno, Isamu Hoshino, Hajime Yokota, Yasukuni Mori, Kohei Wakamatsu, Hiroki Suyari
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Scientific Reports
Scientific Reports
The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-s