Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Takayuki Katsuki"'
Autor:
Jun Kuroda, Masaki Ono, Kyoichi Haida, Masaki Makino, Atsushi Suzuki, Akira Koseki, Ryosuke Yanagiya, Kiyotaka Hoshinaga, Eiichi Saitoh, Ryo Yoshimoto, Takayuki Katsuki, Toshinari Itoko, Yukio Yuzawa, Michiharu Kudo
Publikováno v:
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
Scientific Reports
Scientific Reports
Artificial intelligence (AI) is expected to support clinical judgement in medicine. We constructed a new predictive model for diabetic kidney diseases (DKD) using AI, processing natural language and longitudinal data with big data machine learning, b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56a94afbda23f47f510778af099f7dd8
http://link.springer.com/article/10.1038/s41598-019-48263-5
http://link.springer.com/article/10.1038/s41598-019-48263-5
Autor:
Masaki, Ono, Takayuki, Katsuki, Masaki, Makino, Kyoichi, Haida, Atsushi, Suzuki, Reitaro, Tokumasu
Publikováno v:
Studies in health technology and informatics. 270
In this paper, we propose feature extraction method for prediction model for at the early stage of diabetic kidney disease (DKD) progression. DKD needs continuous treatment; however, a hospital visit interval of a patient at the early stage of DKD is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::f1ec4e692c5ce7aa94da2c8d24f6428b
https://pubmed.ncbi.nlm.nih.gov/32570623
https://pubmed.ncbi.nlm.nih.gov/32570623
Publikováno v:
Studies in health technology and informatics. 270
We propose mini-batch top-n k-medoids to sequential pattern mining to improve CGM interpretation. Mecical workers can treat specific patient groups better by understanding the time series variation of blood glucose results. For 10 years, continuous g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::e9c029e749fa13c514cbea5313013092
https://pubmed.ncbi.nlm.nih.gov/32570390
https://pubmed.ncbi.nlm.nih.gov/32570390
Publikováno v:
ICASSP
This paper addresses the learning task of estimating driver drowsiness from the signals of car acceleration sensors. Since even drivers themselves cannot perceive their own drowsiness in a timely manner unless they use burdensome invasive sensors, ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14f91128cf379487693507c59e39b45d
http://arxiv.org/abs/2005.05898
http://arxiv.org/abs/2005.05898
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 18:1700-1712
Traffic velocity is a fundamental metric for inferring traffic conditions. This paper proposes a new velocity estimation approach from temporal sequences of vehicle count that does not require tracking any vehicles or using any labeled data. It is us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0aa5f7aa355b0b142dc8f7c640da07e1
https://doi.org/10.1109/tits.2016.2628384
https://doi.org/10.1109/tits.2016.2628384
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 18:950-959
We present a new approach to lightweight intelligent transportation systems. Our approach does not rely on traditional expensive infrastructures, but rather on advanced machine learning algorithms. It takes images from traffic cameras at a limited nu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02297f3b52abddbccb2d232b57cc53b9
https://doi.org/10.1109/tits.2016.2597160
https://doi.org/10.1109/tits.2016.2597160
Autor:
Ryosuke Yanagiya, Jun Kuroda, Kyoichi Haida, Akira Koseki, Masaki Ono, Atsushi Suzuki, Toshinari Itoko, Michiharu Kudo, Takayuki Katsuki, Masaki Makino
Publikováno v:
Diabetes. 67
Background: Diabetic kidney diseases (DKD) including diabetic nephropathy is the most frequent cause of hemodialysis (HD), and more precise prediction model could be useful to early intervention of DKD. Methods: We constructed new prediction model fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9e9d2ea4697bef487b99ed4ed43454a
https://doi.org/10.2337/db18-539-p
https://doi.org/10.2337/db18-539-p
Autor:
Takayuki, Katsuki, Masaki, Ono, Akira, Koseki, Michiharu, Kudo, Kyoichi, Haida, Jun, Kuroda, Masaki, Makino, Ryosuke, Yanagiya, Atsushi, Suzuki
Publikováno v:
Studies in health technology and informatics. 247
This paper describes a technology for predicting the aggravation of diabetic nephropathy from electronic health record (EHR). For the prediction, we used features extracted from event sequence of lab tests in EHR with a stacked convolutional autoenco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8c0e8cf9e030a0bab4297b85e1699a2d
https://pubmed.ncbi.nlm.nih.gov/29677932
https://pubmed.ncbi.nlm.nih.gov/29677932
Autor:
Tsuneo Kato, Yosuke Toyota, Hironobu Takagi, Tetsuro Morimura, Daisuke Sato, Takayuki Katsuki
Publikováno v:
ICPR
Older adults who have never used smartphone often suffers from getting used to smartphone gestures because of their lack of basic knowledge or skills with the latest technologies like gesture-oriented touchscreens. In this paper, we propose a user mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f68e0a0f4b11c92548448c2a22a494a4
https://doi.org/10.1109/icpr.2016.7900106
https://doi.org/10.1109/icpr.2016.7900106
Autor:
Masato Inoue, Takayuki Katsuki
Publikováno v:
ICPR
This paper addresses a problem in which we learn a regression model from sets of training data. Each of the sets has an only single label, and only one of the training data in the set reflects the label. This is particularly the case when the label i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed7079646261bd02ae52f1e056dcb7c8
https://doi.org/10.1109/icpr.2016.7900024
https://doi.org/10.1109/icpr.2016.7900024