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Yu-ye Li

Biographic Data

ID7277035
NAMEYu-ye Li
GIVEN NAMESYu-ye
FAMILY NAMELi
SIGNATURELI Y
AFFILIATIONSDepartment of Dermatology Venereology, First Affiliated Hospital of Kunming Medical University
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Machine learning methods to predict leprosy misdiagnosis in Yunnan Province, People's Republic of China

    Open Access•Yingwu Guo, Lijiao Yin et al.•ARTICLE•Frontiers in Public Health•2026

    Background and objective: that is often misdiagnosed. This study aimed to identify factors associated with leprosy misdiagnosis and develop and compare machine learning (ML) models to predict the risk of misdiagnosis. Methods: A retrospective analysis was conducted on clinical and epidemiological data in 486 diagnosed leprosy patients. The outcome was a binary variable to indicate whether a patient had experienced a prior misdiagnosis. Features a…

  • Dingxin recipe III ameliorates hyperlipidemia injury in SD rats by improving the gut barrier, particularly the SCFAs/GPR43 pathway

    Open Access•Yuyan Gu, Yu-yan Gu et al.•ARTICLE•Journal of Ethnopharmacology•2023

    DXR III protects against hyperlipidemia by improving the gut barrier, particularly the SCFAs/GPR43 pathway

  • Deep Fungal Infections Among General Hospital Inpatients in Southwestern China

    Open Access•Shu-Ran Wen, Zheng-Hui Yang et al.•ARTICLE•Frontiers in Public Health•2022

    Background Deep fungal infection is a type of life-threatening opportunistic infection. Its incidence has been increasing in recent years. This infection can affect the prognosis of patients, prolong hospital stays and raise costs for patients and their families. Objective We aimed to understand the current situation of deep fungal infections in the First Affiliated Hospital of Kunming Medical University and to provide a basis for the clinical di…

  • Factors Influencing Leprosy Incidence

    Open Access•Yu-ye Li, Yu‐Ye Li et al.•ARTICLE•Frontiers in Public Health•2021

    Leprosy remains endemic in some regions and is a global health concern. However, the possible causes and risk factors of the disease remain unclear. Data in Wenshan, China were collected from the Wenshan Institute of Dermatology (1986–2015); data in Nepal were obtained from the Leprosy Control Division, Department of Health Services, Nepal (2011 to 2015); and data from Indonesia, India, and Brazil were collected from WHO records. We assessed the …

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  • Factors Influencing Leprosy Incidence

    Open Access•Yu-ye Li, Yu‐Ye Li et al.•ARTICLE•Frontiers in Public Health•2021

    Leprosy remains endemic in some regions and is a global health concern. However, the possible causes and risk factors of the disease remain unclear. Data in Wenshan, China were collected from the Wenshan Institute of Dermatology (1986–2015); data in Nepal were obtained from the Leprosy Control Division, Department of Health Services, Nepal (2011 to 2015); and data from Indonesia, India, and Brazil were collected from WHO records. We assessed the …

  • Deep Fungal Infections Among General Hospital Inpatients in Southwestern China

    Open Access•Shu-Ran Wen, Zheng-Hui Yang et al.•ARTICLE•Frontiers in Public Health•2022

    Background Deep fungal infection is a type of life-threatening opportunistic infection. Its incidence has been increasing in recent years. This infection can affect the prognosis of patients, prolong hospital stays and raise costs for patients and their families. Objective We aimed to understand the current situation of deep fungal infections in the First Affiliated Hospital of Kunming Medical University and to provide a basis for the clinical di…

  • Dingxin recipe III ameliorates hyperlipidemia injury in SD rats by improving the gut barrier, particularly the SCFAs/GPR43 pathway

    Open Access•Yuyan Gu, Yu-yan Gu et al.•ARTICLE•Journal of Ethnopharmacology•2023

    DXR III protects against hyperlipidemia by improving the gut barrier, particularly the SCFAs/GPR43 pathway

  • Machine learning methods to predict leprosy misdiagnosis in Yunnan Province, People's Republic of China

    Open Access•Yingwu Guo, Lijiao Yin et al.•ARTICLE•Frontiers in Public Health•2026

    Background and objective: that is often misdiagnosed. This study aimed to identify factors associated with leprosy misdiagnosis and develop and compare machine learning (ML) models to predict the risk of misdiagnosis. Methods: A retrospective analysis was conducted on clinical and epidemiological data in 486 diagnosed leprosy patients. The outcome was a binary variable to indicate whether a patient had experienced a prior misdiagnosis. Features a…

Medicine (3 works) · China (2 works) · Epidemiology (2 works) · Geography (2 works) · Leprosy (2 works) · Leprosy Research and Treatment (2 works) · Antifungal resistance and susceptibility (1 work) · Chemistry (1 work) · Cutaneous Melanoma Detection and Management (1 work) · Demography (1 work)

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