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Xinru Tao

Biographic Data

ID7301755
NAMEXinru Tao
GIVEN NAMESXinru
FAMILY NAMETao
SIGNATURETAO X
AFFILIATIONSZaozhuang University
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2025
LATEST PUBLICATION YEAR2026
H-INDEX0
  • A study on promoting AI learning and usage behaviors among health management students from the perspective of the “knowledge-belief-action” model

    Open Access•Jinsong Du, Le Zhu et al.•ARTICLE•Frontiers in Public Health•2026

    Introduction: The application of Artificial Intelligence (AI) in the field of health management is becoming increasingly widespread, driving health services toward precision, personalization, and intelligence. This study aims to explore the behavior patterns of health management college students in AI learning and device usage. In addition, the study also aims to enhance students' motivation and ability to apply AI by constructing a feedback orie…

  • A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology

    Open Access•Jinsong Du, Xinru Tao et al.•ARTICLE•Frontiers in Public Health•2025

    Introduction: Middle-aged and older adults are highly susceptible to depression. For this reason, early identification and intervention can substantially reduce its prevalence. This study innovatively proposed a visual risk prediction system for depressive symptoms and depression in middle-aged and older adults, rooted in machine learning and visualization technologies. Methods: Using cohort data from the China Health and Retirement Longitudinal …

  • Development of a visualized risk prediction system for sarcopenia in older adults using machine learning

    Open Access•Jinsong Du, Xinru Tao et al.•ARTICLE•Frontiers in Public Health•2025

    Introduction: The older adult are at high risk of sarcopenia, making early identification and scientific intervention crucial for healthy aging. Methods: This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), including a cohort of 2,717 middle-aged and older adult participants. Ten machine learning algorithms, such as CatBoost, XGBoost, and NGBoost, were used to construct predictive models. Results: Among these…

  • Concerted inhibition of mTorc1/2 and NF-κB by Yuye Jiedu granule via AMPK activation and PI3K/Akt suppression

    Open Access•Xiaolong Feng, Xinru Tao et al.•ARTICLE•Journal of Ethnopharmacology•2025

No prominent works on this page.

  • A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology

    Open Access•Jinsong Du, Xinru Tao et al.•ARTICLE•Frontiers in Public Health•2025

    Introduction: Middle-aged and older adults are highly susceptible to depression. For this reason, early identification and intervention can substantially reduce its prevalence. This study innovatively proposed a visual risk prediction system for depressive symptoms and depression in middle-aged and older adults, rooted in machine learning and visualization technologies. Methods: Using cohort data from the China Health and Retirement Longitudinal …

  • Development of a visualized risk prediction system for sarcopenia in older adults using machine learning

    Open Access•Jinsong Du, Xinru Tao et al.•ARTICLE•Frontiers in Public Health•2025

    Introduction: The older adult are at high risk of sarcopenia, making early identification and scientific intervention crucial for healthy aging. Methods: This study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), including a cohort of 2,717 middle-aged and older adult participants. Ten machine learning algorithms, such as CatBoost, XGBoost, and NGBoost, were used to construct predictive models. Results: Among these…

  • Concerted inhibition of mTorc1/2 and NF-κB by Yuye Jiedu granule via AMPK activation and PI3K/Akt suppression

    Open Access•Xiaolong Feng, Xinru Tao et al.•ARTICLE•Journal of Ethnopharmacology•2025

  • A study on promoting AI learning and usage behaviors among health management students from the perspective of the “knowledge-belief-action” model

    Open Access•Jinsong Du, Le Zhu et al.•ARTICLE•Frontiers in Public Health•2026

    Introduction: The application of Artificial Intelligence (AI) in the field of health management is becoming increasingly widespread, driving health services toward precision, personalization, and intelligence. This study aims to explore the behavior patterns of health management college students in AI learning and device usage. In addition, the study also aims to enhance students' motivation and ability to apply AI by constructing a feedback orie…

Medicine (3 works) · Artificial Intelligence (2 works) · Cohort (2 works) · Cohort study (2 works) · Computer Science (2 works) · Gerontology (2 works) · Interpretability (2 works) · Longitudinal study (2 works) · Machine learning (2 works) · Pathology (2 works)

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