ArticleProceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems2017
Mining Public Datasets for Modeling Intra-City PM
Article in Proceedings of the ... ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems : ACM GIS. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Patterns Discovery Dataset for Particulate Matter (PMScientific data · 2025Article
- Opportunities and shortcomings of AI for spatial epidemiology and health disparities research on aging and the life course.Health & place · 2024Article
- Prediction Tool on Fine Particle Pollutants and Air Quality for Environmental Engineering.SN computer science · 2022Article
- Modelling the impact of MAUP on environmental drivers for Schistosoma japonicum prevalence.Parasites & vectors · 2020Article
- Integration of Remote Sensing and Social Sensing Data in a Deep Learning Framework for Hourly Urban PMInternational journal of environmental research and public health · 2019Article
- Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.Environment international · 2019Article
- Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.Environmental health : a global access science source · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Air quality models are important for studying the impact of air pollutant on health conditions at a fine spatiotemporal scale. Existing work typically relies on area-specific, expert-selected attributes of pollution emissions (e,g., transportation) and dispersion (e.g., meteorology) for building the model for each combination of study areas, pollutant types, and spatiotemporal scales. In this paper, we present a data mining approach that utilizes publicly available OpenStreetMap (OSM) data to automatically generate an air quality model for the concentrations of fine particulate matter less than 2.5
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.