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Nobuo Fuse

Biographic Data

ID6169003
NAMENobuo Fuse
GIVEN NAMESNobuo
FAMILY NAMEFuse
SIGNATUREFUSE N
AFFILIATIONSTohoku Medical Megabank Organization
ORCID0000-0003-0237-4746
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS0
AUTHOR COUNT5
EDITOR COUNT0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Significant Correlation Between White Matter Hyperintensity Volume and Rare NOTCH3 Variants in the General Japanese Population

    Open Access•Ikuko Mizuta, Fumio Yamashita et al.•ARTICLE•Geriatrics and gerontology…•2026

  • Degree of housing damage caused by the Great East Japan Earthquake and all-cause mortality in the community-based cohort study of the Tohoku Medical Megabank Project

    Naoki Nakaya, Kumi Nakaya et al.•ARTICLE•Journal of Epidemiology and…•2025•References: 38

    BACKGROUND: Natural disasters may have negative health effects on survivors. However, long-term observations on this are lacking. Therefore, this study investigated the association between the degree of housing damage caused by the Great East Japan Earthquake (GEJE) and all-cause mortality using the data from the cohort study conducted by the Tohoku Medical Megabank (TMM) Project in disaster-stricken areas. METHODS: The community-based cohort stu…

  • Association of physiological factors with grip and leg extension strength

    Open Access•Yoshiaki Noji, Rieko Hatanaka et al.•ARTICLE•BMC Public Health•2024

    Grip and leg extension strength demonstrated similar associations with anthropometry, pulmonary function, and estimated glomerular filtration rate, but the associations with the other factors were not always consistent

  • Comprehensive evaluation of machine learning algorithms for predicting sleep–wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate…

    Open Access•Xue Li, Chiaki Ono et al.•ARTICLE•Frontiers in Psychiatry•2023

    In the test for predicting three types of sleep-wake conditions, most of the algorithms, except for Naïve Bayes, showed higher areas under the curve (AUCs; 0.82-0.88) and accuracy (0.78-0.81). The test using four types of sleep-wake conditions with differentiation between the wake conditions before and after sleep also resulted in successful prediction by the gated recurrent unit with the highest AUC (0.86) and accuracy (0.79). Among the nine fea…

  • Heart Rate Information-Based Machine Learning Prediction of Emotions Among Pregnant Women

    Open Access•Xue Li, Chiaki Ono et al.•ARTICLE•Frontiers in Psychiatry•2022

    In this study, the extent to which different emotions of pregnant women can be predicted based on heart rate-relevant information as indicators of autonomic nervous system functioning was explored using various machine learning algorithms. Nine heart rate-relevant autonomic system indicators, including the coefficient of variation R-R interval (CVRR), standard deviation of all NN intervals (SDNN), and square root of the mean squared differences o…

No prominent works on this page.

  • Heart Rate Information-Based Machine Learning Prediction of Emotions Among Pregnant Women

    Open Access•Xue Li, Chiaki Ono et al.•ARTICLE•Frontiers in Psychiatry•2022

    In this study, the extent to which different emotions of pregnant women can be predicted based on heart rate-relevant information as indicators of autonomic nervous system functioning was explored using various machine learning algorithms. Nine heart rate-relevant autonomic system indicators, including the coefficient of variation R-R interval (CVRR), standard deviation of all NN intervals (SDNN), and square root of the mean squared differences o…

  • Comprehensive evaluation of machine learning algorithms for predicting sleep–wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate…

    Open Access•Xue Li, Chiaki Ono et al.•ARTICLE•Frontiers in Psychiatry•2023

    In the test for predicting three types of sleep-wake conditions, most of the algorithms, except for Naïve Bayes, showed higher areas under the curve (AUCs; 0.82-0.88) and accuracy (0.78-0.81). The test using four types of sleep-wake conditions with differentiation between the wake conditions before and after sleep also resulted in successful prediction by the gated recurrent unit with the highest AUC (0.86) and accuracy (0.79). Among the nine fea…

  • Association of physiological factors with grip and leg extension strength

    Open Access•Yoshiaki Noji, Rieko Hatanaka et al.•ARTICLE•BMC Public Health•2024

    Grip and leg extension strength demonstrated similar associations with anthropometry, pulmonary function, and estimated glomerular filtration rate, but the associations with the other factors were not always consistent

  • Degree of housing damage caused by the Great East Japan Earthquake and all-cause mortality in the community-based cohort study of the Tohoku Medical Megabank Project

    Naoki Nakaya, Kumi Nakaya et al.•ARTICLE•Journal of Epidemiology and…•2025•References: 38

    BACKGROUND: Natural disasters may have negative health effects on survivors. However, long-term observations on this are lacking. Therefore, this study investigated the association between the degree of housing damage caused by the Great East Japan Earthquake (GEJE) and all-cause mortality using the data from the cohort study conducted by the Tohoku Medical Megabank (TMM) Project in disaster-stricken areas. METHODS: The community-based cohort stu…

  • Significant Correlation Between White Matter Hyperintensity Volume and Rare NOTCH3 Variants in the General Japanese Population

    Open Access•Ikuko Mizuta, Fumio Yamashita et al.•ARTICLE•Geriatrics and gerontology…•2026

Internal Medicine (4 works) · Medicine (4 works) · Artificial Intelligence (2 works) · Computer Science (2 works) · Engineering (2 works) · Heart rate (2 works) · Heart rate variability (2 works) · Heart Rate Variability and Autonomic Control (2 works) · Machine learning (2 works) · Neonatal and fetal brain pathology (2 works)

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