Zobrazeno 1 - 10 of 50 pro vyhledávání: '"Masayuki NAMBU"'
1
Akademický článek
Investigation on factors related to poor CPAP adherence using machine learning: a pilot study
Autor: Kana Eguchi, Tsutomu Yabuuchi, Masayuki Nambu, Hirofumi Takeyama, Shozo Azuma, Kazuo Chin, Tomohiro Kuroda
Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract To improve patients’ adherence to continuous positive airway pressure (CPAP) therapy, this study aimed to clarify whether machine learning-based data analysis can identify the factors related to poor CPAP adherence (i.e., CPAP usage that d
Externí odkaz: https://doaj.org/article/9da32ceadfc54b7288f33009b1f6d1cd
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2
Akademický článek
Token Economy–Based Hospital Bed Allocation to Mitigate Information Asymmetry: Proof-of-Concept Study Through Simulation Implementation
Autor: Shusuke Hiragi, Jun Hatanaka, Osamu Sugiyama, Kenichi Saito, Masayuki Nambu, Tomohiro Kuroda
Publikováno v: JMIR Formative Research, Vol 6, Iss 3, p e28877 (2022)
BackgroundHospital bed management is an important resource allocation task in hospital management, but currently, it is a challenging task. However, acquiring an optimal solution is also difficult because intraorganizational information asymmetry exi
Externí odkaz: https://doaj.org/article/98cf779f55bb426dbe14b78e8e7340bb
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3
Akademický článek
Understanding the EMR-Related Experiences of Pregnant Japanese Women to Redesign Antenatal Care EMR Systems
Autor: Samar Helou, Victoria Abou-Khalil, Goshiro Yamamoto, Eiji Kondoh, Hiroshi Tamura, Shusuke Hiragi, Osamu Sugiyama, Kazuya Okamoto, Masayuki Nambu, Tomohiro Kuroda
Publikováno v: Informatics, Vol 6, Iss 2, p 15 (2019)
Woman-centered antenatal care necessitates Electronic Medical Record (EMR) systems that respect women’s preferences. However, women’s preferences regarding EMR systems in antenatal care remain unknown. This work aims to understand the EMR-related
Externí odkaz: https://doaj.org/article/7a4c0229be814a8db59d69d91ecd7ee0
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6
Token Economy–Based Hospital Bed Allocation to Mitigate Information Asymmetry: Proof-of-Concept Study Through Simulation Implementation (Preprint)
Autor: Shusuke Hiragi, Jun Hatanaka, Osamu Sugiyama, Kenichi Saito, Masayuki Nambu, Tomohiro Kuroda
BACKGROUND Hospital bed management is an important resource allocation task in hospital management, but currently, it is a challenging task. However, acquiring an optimal solution is also difficult because intraorganizational information asymmetry ex
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e5457c7954477a4b991143d6ec144037
https://doi.org/10.2196/preprints.28877
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7
Token Economy-Based Hospital Bed Allocation to Mitigate Information Asymmetry: Proof-of-Concept Study Through Simulation Implementation
Autor: Shusuke Hiragi, Jun Hatanaka, Osamu Sugiyama, Kenichi Saito, Masayuki Nambu, Tomohiro Kuroda
Publikováno v: JMIR formative research. 6(3)
Background Hospital bed management is an important resource allocation task in hospital management, but currently, it is a challenging task. However, acquiring an optimal solution is also difficult because intraorganizational information asymmetry ex
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c8b4a8287080629bdddfbd7ca2872e4
https://pubmed.ncbi.nlm.nih.gov/35254264
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9
Akademický článek
Prediction of Polyphonic Alarm Sound by Deep Neural Networks. (English)
Autor: Kazumasa KISHIMOTO, Tadamasa TAKEMURA, Osamu SUGIYAMA, Ryosuke KOJIMA, Masahiro YAKAMI, Masayuki NAMBU, Kiyotaka FUJII, Tomohiro KURODA
Publikováno v: Transactions of Japanese Society for Medical & Biological Engineering; 2022, Vol. 60 Issue 1, p8-15, 8p
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10
Early Nephrosis Detection Based on Deep Learning with Clinical Time-Series Data
Autor: Yohei, Yamasaki, Osamu, Sugiyama, Shusuke, Hiragi, Shosuke, Ohtera, Goshiro, Yamamoto, Hiroshi, Sasaki, Kazuya, Okamoto, Masayuki, Nambu, Tomohiro, Kuroda
Publikováno v: Studies in health technology and informatics. 264
Nephrosis is disease characterized by abnormal protein loss from impaired kidney. We constructed early prediction model using machine learning from clinical time series data, that can predict onset of nephrosis for more than one month. Long short-ter
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::fedcdc151543f38596067894d3317392
https://pubmed.ncbi.nlm.nih.gov/31438249
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