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Deyang Li

Biographic Data

ID7180136
NAMEDeyang Li
GIVEN NAMESDeyang
FAMILY NAMELi
SIGNATURELI D
AFFILIATIONSChinese Academy of Sciences
ORCID0000-0002-3670-4590
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Application of the PDCA cycle management in quality improvement of endotracheal intubation in emergency department among standardised training residents

    Open Access•Zhanpeng Tan, Fang Lai et al.•ARTICLE•BMC Medical Education•2026

    BACKGROUND: Endotracheal intubation (ETI) stands as a cornerstone intervention within the emergency department, yet its efficacy can be undermined by a myriad of variables. For patients teetering on the brink of critical illness, securing the endotracheal tube during the initial attempt is not merely preferable but imperative. Consequently, elevating the first-pass success (FPS) rate achieved by emergency physicians becomes a vital strategy to cu…

  • Interactions Between Depressive Symptoms, Childhood Trauma, and Drug Craving in Chinese Men with Methamphetamine Use Disorder

    Deyang Li, Dongmei Wang et al.•ARTICLE•Journal of Psychoactive Drugs•2025

    Drug craving in methamphetamine use disorder (MAUD) patients is influenced by various adverse psychological problems. This study adopted network analysis to investigate the interrelationships between psychological correlates and drug craving and identify the critical pathways between them. A total of 757 men with MAUD were recruited from a drug rehabilitation center in southwest China. They completed self-report scales to measure emotion regulati…

  • Construction of Xinjiang metabolic syndrome risk prediction model based on interpretable models

    Open Access•Yan Zhang, Jaina Razbek et al.•ARTICLE•BMC Public Health•2022

    Both DT and LR MetS risk prediction models have good prediction performance and their respective characteristics. Combining these two methods to construct an interpretable risk prediction model of MetS can provide methodological references for the prevention and control of MetS

No prominent works on this page.

  • Construction of Xinjiang metabolic syndrome risk prediction model based on interpretable models

    Open Access•Yan Zhang, Jaina Razbek et al.•ARTICLE•BMC Public Health•2022

    Both DT and LR MetS risk prediction models have good prediction performance and their respective characteristics. Combining these two methods to construct an interpretable risk prediction model of MetS can provide methodological references for the prevention and control of MetS

  • Interactions Between Depressive Symptoms, Childhood Trauma, and Drug Craving in Chinese Men with Methamphetamine Use Disorder

    Deyang Li, Dongmei Wang et al.•ARTICLE•Journal of Psychoactive Drugs•2025

    Drug craving in methamphetamine use disorder (MAUD) patients is influenced by various adverse psychological problems. This study adopted network analysis to investigate the interrelationships between psychological correlates and drug craving and identify the critical pathways between them. A total of 757 men with MAUD were recruited from a drug rehabilitation center in southwest China. They completed self-report scales to measure emotion regulati…

  • Application of the PDCA cycle management in quality improvement of endotracheal intubation in emergency department among standardised training residents

    Open Access•Zhanpeng Tan, Fang Lai et al.•ARTICLE•BMC Medical Education•2026

    BACKGROUND: Endotracheal intubation (ETI) stands as a cornerstone intervention within the emergency department, yet its efficacy can be undermined by a myriad of variables. For patients teetering on the brink of critical illness, securing the endotracheal tube during the initial attempt is not merely preferable but imperative. Consequently, elevating the first-pass success (FPS) rate achieved by emergency physicians becomes a vital strategy to cu…

Medicine (2 works) · Addiction (1 works) · Airway (1 works) · Airway management (1 works) · Anthropometry (1 works) · Artificial Intelligence in Healthcare (1 works) · Best practice (1 works) · Biostatistics (1 works) · Blood pressure (1 works) · Cardiovascular Health and Risk Factors (1 works)

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