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Yuting Gu

Biographic Data

ID8311174
NAMEYuting Gu
GIVEN NAMESYuting
FAMILY NAMEGu
SIGNATUREGU Y
AFFILIATIONSIrvine University
ORCID0009-0003-2431-1030
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2026
H-INDEX0
  • The accent atlas

    Open Access•Yuting Gu, Seth Cutler et al.•ARTICLE•Psychonomic Bulletin & Review•2026

  • The clinical value of inflammation index in predicting ICU mortality of critically ill patients with intracerebral hemorrhage

    Open Access•Guang Zhao, Yuting Gu et al.•ARTICLE•Frontiers in Public Health•2024

    Background: The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic …

  • Machine learning models including insulin resistance indexes for predicting liver stiffness in United States population

    Open Access•Kexing Han, Kexuan Tan et al.•ARTICLE•Frontiers in Public Health•2022

    Background: Prevention and treatment of liver fibrosis at an early stage is of great prognostic importance, whereas changes in liver stiffness are often overlooked in patients before the onset of obvious clinical symptoms. Recognition of liver fibrosis at an early stage is therefore essential. Objective: An XGBoost machine learning model was constructed to predict participants' liver stiffness measures (LSM) from general characteristic informatio…

No prominent works on this page.

  • Machine learning models including insulin resistance indexes for predicting liver stiffness in United States population

    Open Access•Kexing Han, Kexuan Tan et al.•ARTICLE•Frontiers in Public Health•2022

    Background: Prevention and treatment of liver fibrosis at an early stage is of great prognostic importance, whereas changes in liver stiffness are often overlooked in patients before the onset of obvious clinical symptoms. Recognition of liver fibrosis at an early stage is therefore essential. Objective: An XGBoost machine learning model was constructed to predict participants' liver stiffness measures (LSM) from general characteristic informatio…

  • The clinical value of inflammation index in predicting ICU mortality of critically ill patients with intracerebral hemorrhage

    Open Access•Guang Zhao, Yuting Gu et al.•ARTICLE•Frontiers in Public Health•2024

    Background: The inflammatory response holds paramount significance in the context of intracerebral hemorrhage (ICH) and exhibits a robust correlation with mortality rates. Biological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) play crucial roles in influencing the systemic …

  • The accent atlas

    Open Access•Yuting Gu, Seth Cutler et al.•ARTICLE•Psychonomic Bulletin & Review•2026

Internal Medicine (2 works) · Medicine (2 works) · Artificial Intelligence (1 work) · Cohort (1 work) · Comprehension (1 work) · Computer Science (1 work) · Critically ill (1 work) · Environmental health (1 work) · Fibrosis (1 work) · Inflammation (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae