Pulse Entdecken nav.journalClub Debatten Trends Forschende Zeitschriften

Join discussions, follow papers, and never miss your next session.

Download on theApp Store

Start Entdecken nav.journalClub Trends

⌘+K

January 31, 2025Open Access

View Full Paper

Machine learning-enhanced high-resolution exposure assessment of ultrafine particles

YJYudie JianyaoTsinghua University HYHongyong YuanHefei University GSGuofeng SuMidea Group (China)

Key Points

Key points are not available for this paper at this time.

Abstract

. These findings provide crucial insights for the development of future UFP standards.

KI fragen

Like

Bookmark

Share

View Full Paper

KI fragen

Like

Bookmark

Share

View Full Paper

Cite This Study

Jianyao et al. (Fri,) studied this question.

synapsesocial.com/papers/6a036edbc24a02571486ccef https://doi.org/https://doi.org/10.1038/s41467-025-56581-8

Machine learning-enhanced high-resolution exposure assessment of ultrafine particles | Synapse

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Understanding biophysicochemical interactions at the nano–bio interface2009 · 6,983 citations
2Ultrafine (nanometre) particle mediated lung injury1998 · 784 citations
3Harnessing AI to unmask Copenhagen's invisible air pollutants: A study on three ultrafine particle metrics2024 · 8 citations
4High spatial resolution land-use regression model for urban ultrafine particle exposure assessment in Shanghai, China2021 · 40 citations
5Development of land-use regression models for exposure assessment to ultrafine particles in Rome, Italy2017 · 55 citations