Liyuan Ge

Biographic Data

ID10006941
NAMELiyuan Ge
GIVEN NAMESLiyuan
FAMILY NAMEGe
SIGNATUREGE L
AFFILIATIONSGuilin Medical University
ORCID0000-0002-5158-0311
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2026
LATEST PUBLICATION YEAR2026
H-INDEX0

  • Survival time and influencing factors among people living with HIV in Guilin City, Guangxi, China

    Open AccessYan Feng, Ge Li et al.ARTICLEFrontiers in Public Health2026

    Background: Despite significant advances in antiretroviral therapy (ART), substantial disparities in survival outcomes among people living with HIV (PLWH) persist in resource-limited settings. However, in Guangxi, a region heavily affected by the HIV/AIDS epidemic in China, research on the survival time of PLWH and its associated factors remains limited. This study aims to investigate the survival time and its influencing factors among PLWH in Gu…

  • Development and testing of a smart empowerment education system for gout patients in suburban areas

    Open AccessTao Jiang, Liyuan Ge et al.ARTICLEFrontiers in Public Health2026

    Objectives This study aimed to develop and evaluate an Intelligent Empowerment Education-based System (IEES), which integrates empowerment education, refined management protocols, and smart technologies, for application among gout patients in resource-limited suburban settings. The primary goal was to address key challenges including suboptimal self-management capacity, poor treatment adherence, and unfavorable long-term clinical outcomes. Method…

  • Research on daily medication and drug efficacy evaluation for chronic diseases based on natural language processing (NLP)

    Open AccessTao Jiang, Zhini Yu et al.ARTICLEFrontiers in Public Health2026

    Objectives: This study aims to harness Natural Language Processing (NLP) to improve chronic disease medication management, focusing on the antihypertensive drug Lisinopril. The objectives are: (1) to develop an intelligent drug safety monitoring and personalized intervention platform integrating patient feedback; (2) to accurately identify drug side effects and analyze their associations with patient demographics; and (3) to build a personalized …

  • Enhancing diabetes risk stratification through natural language processing

    Open AccessYaoyan Lu, Tingting Li et al.ARTICLEFrontiers in Public Health2026

    Background This study investigates whether integrating Natural Language Processing (NLP) with traditional clinical data improves type 2 diabetes risk prediction by extracting latent risk factors from unstructured medical text. Methods We analyzed a public dataset of 1,879 individuals. Structured variables (BMI, HbA1c, blood pressure) were normalized, while unstructured textual entries (symptom descriptions, lifestyle notes) were processed using a…