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Meilin Yang

Datos Biográficos

ID4417872
NOMBREMeilin Yang
NOMBRESMeilin
APELLIDOYang
FIRMAYANG M
AFILIACIONESInstitute for Urban and Regional Research
VERIFICADONo
TOTAL DE OBRAS3
TOTAL DE CITAS0
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2008
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H0
  • Leveraging LLMs and explainable AI to decode citizen complaints for neighborhood respiratory health prediction

    Open Access•Haoxiang Zhao, Junhan Hu et al.•ARTICLE•Health & Place•2026•Referencias: 3

    Respiratory illnesses pose spatially varying threats to human well-being, yet effective monitoring approaches remain limited. This study introduces a novel, place-based framework for predicting neighborhood-level respiratory health by decoding citizen complaints. Utilizing 2.3 million 311 non-urgent service request records in New York City, we demonstrate that citizen complaints outperform conventional census-derived variables in predicting censu…

  • Impacts of the built environment on remote work choices and preferences

    Open Access•Meilin Yang, Yunhan Zheng et al.•ARTICLE•Cities•2025•Referencias: 1

  • Holocene moisture evolution in arid central Asia and its out-of-phase relationship with Asian monsoon history

    Open Access•Fahu Chen, Zicheng Yu et al.•ARTICLE•Quaternary Science Reviews•2008

Sin obras prominentes en esta página.

  • Holocene moisture evolution in arid central Asia and its out-of-phase relationship with Asian monsoon history

    Open Access•Fahu Chen, Zicheng Yu et al.•ARTICLE•Quaternary Science Reviews•2008

  • Impacts of the built environment on remote work choices and preferences

    Open Access•Meilin Yang, Yunhan Zheng et al.•ARTICLE•Cities•2025•Referencias: 1

  • Leveraging LLMs and explainable AI to decode citizen complaints for neighborhood respiratory health prediction

    Open Access•Haoxiang Zhao, Junhan Hu et al.•ARTICLE•Health & Place•2026•Referencias: 3

    Respiratory illnesses pose spatially varying threats to human well-being, yet effective monitoring approaches remain limited. This study introduces a novel, place-based framework for predicting neighborhood-level respiratory health by decoding citizen complaints. Utilizing 2.3 million 311 non-urgent service request records in New York City, we demonstrate that citizen complaints outperform conventional census-derived variables in predicting censu…

Air Quality and Health Impacts (1 obras) · Archaeology and ancient environmental studies (1 obras) · Arid (1 obras) · Climate change (1 obras) · Climatology (1 obras) · Complaint (1 obras) · Computer Science (1 obras) · Conversation (1 obras) · COVID-19 epidemiological studies (1 obras) · Data-Driven Disease Surveillance (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