Saltar al contenido principal

ETHNOS_APP

Inicio • Búsqueda • Revistas • Lista 0

Bocheng Jing

Datos Biográficos

ID5542228
NOMBREBocheng Jing
NOMBRESBocheng
APELLIDOJing
FIRMAJING B
AFILIACIONESSan Francisco VA Health Care System
ORCID0000-0002-2021-5055
VERIFICADOSí
TOTAL DE OBRAS3
TOTAL DE CITAS0
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2019
AÑO MÁS RECIENTE DE PUBLICACIÓN2024
ÍNDICE H0
  • Effects of residential socioeconomic polarization on high blood pressure among nursing home residents

    Open Access•Hoda S Abdel Magid, Samuel Jaros et al.•ARTICLE•Health & Place•2024•Referencias: 11

  • Comparing Machine Learning to Regression Methods for Mortality Prediction Using Veterans Affairs Electronic Health Record Clinical Data

    Bocheng Jing, W John Boscardin et al.•ARTICLE•Medical Care•2022•Referencias: 33

    BACKGROUND: It is unclear whether machine learning methods yield more accurate electronic health record (EHR) prediction models compared with traditional regression methods. OBJECTIVE: The objective of this study was to compare machine learning and traditional regression models for 10-year mortality prediction using EHR data. DESIGN: This was a cohort study. SETTING: Veterans Affairs (VA) EHR data. PARTICIPANTS: Veterans age above 50 with a prima…

  • Comparison of Pharmacy Database Methods for Determining Prevalent Chronic Medication Use

    Timothy S Anderson, Bocheng Jing et al.•ARTICLE•Medical Care•2019•Referencias: 23

    BACKGROUND: Pharmacy dispensing data are frequently used to identify prevalent medication use as a predictor or covariate in observational research studies. Although several methods have been proposed for using pharmacy dispensing data to identify prevalent medication use, little is known about their comparative performance. OBJECTIVES: The authors sought to compare the performance of different methods for identifying prevalent outpatient medicat…

Sin obras prominentes en esta página.

  • Comparison of Pharmacy Database Methods for Determining Prevalent Chronic Medication Use

    Timothy S Anderson, Bocheng Jing et al.•ARTICLE•Medical Care•2019•Referencias: 23

    BACKGROUND: Pharmacy dispensing data are frequently used to identify prevalent medication use as a predictor or covariate in observational research studies. Although several methods have been proposed for using pharmacy dispensing data to identify prevalent medication use, little is known about their comparative performance. OBJECTIVES: The authors sought to compare the performance of different methods for identifying prevalent outpatient medicat…

  • Comparing Machine Learning to Regression Methods for Mortality Prediction Using Veterans Affairs Electronic Health Record Clinical Data

    Bocheng Jing, W John Boscardin et al.•ARTICLE•Medical Care•2022•Referencias: 33

    BACKGROUND: It is unclear whether machine learning methods yield more accurate electronic health record (EHR) prediction models compared with traditional regression methods. OBJECTIVE: The objective of this study was to compare machine learning and traditional regression models for 10-year mortality prediction using EHR data. DESIGN: This was a cohort study. SETTING: Veterans Affairs (VA) EHR data. PARTICIPANTS: Veterans age above 50 with a prima…

  • Effects of residential socioeconomic polarization on high blood pressure among nursing home residents

    Open Access•Hoda S Abdel Magid, Samuel Jaros et al.•ARTICLE•Health & Place•2024•Referencias: 11

Cohort (3 obras) · Internal Medicine (3 obras) · Medicine (3 obras) · Internal Medicine (2 obras) · Veterans Affairs (2 obras) · Advanced Causal Inference Techniques (1 obras) · Artificial Intelligence (1 obras) · Artificial Intelligence (1 obras) · Artificial Intelligence in Healthcare and Education (1 obras) · Blood pressure (1 obras)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae