Forecasting daily total pollen concentrations on a global scale

Makra, L., Coviello, L., Gobbi, A., Jurman, G., Furlanello, C., Brunato, M., Ziska, L. H., Hess, J. J., Damialis, A., Garcia, M. P. P., Tusnády, G., Czibolya, L., Ihász, I., Deák, Á. J., Mikó, E., Dorner, Z., Harry, S. K., Bruffaerts, N., Packeu, A., … Traidl‐Hoffmann, C. (2024). Forecasting daily total pollen concentrations on a global scale. Allergy, 79(8), 2173–2185. Portico. https://doi.org/10.1111/all.16227
Authors:
László Makra
Luca Coviello
Andrea Gobbi
Giuseppe Jurman
Cesare Furlanello
Mauro Brunato
Lewis H Ziska
Jeremy J Hess
Athanasios Damialis
Maria Pilar Plaza Garcia
Gábor Tusnády
Lilit Czibolya
István Ihász
Áron József Deák
Edit Mikó
Zita Dorner
Susan K Harry
Nicolas Bruffaerts
Ann Packeu
Annika Saarto
Linnea Toiviainen
Maria Louna-Korteniemi
Sanna Pätsi
Michel Thibaudon
Gilles Oliver
Athanasios Charalampopoulos
Despoina Vokou
Ewa Maria Przedpelska-Wasowicz
Ellý Renée Guðjohnsen
Maira Bonini
Sevcan Celenk
Cumali Ozaslan
Jae-Won Oh
Krista Sullivan
Linda Ford
Michelle Kelly
Estelle Levetin
Dorota Myszkowska
Elena Severova
Regula Gehrig
María Del Carmen Calderón-Ezquerro
César Guerrero Guerra
Manuel Andres Leiva-Guzmán
Germán Darío Ramón
Laura Beatriz Barrionuevo
Jonny Peter
Dilys Berman
Connie H Katelaris
Janet M Davies
Pamela Burton
Paul J Beggs
Sandra María Vergamini
Rosa María Valencia-Barrera
Claudia Traidl-Hoffmann
Affiliated Authors:
Lewis H Ziska
Columbia Affiliation:
Subjects:
Pollen (MeSH)
Allergens (MeSH)
Forecasting (MeSH)
Author Keywords:
allergy
artificial intelligence
environmental variables
feature importance cluster
pollen forecast
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Publication Type:
Article
Unique ID:
10.1111/all.16227
PMID:
38995241
DOI:
10.1111/all.16227
Journal:
Allergy
Publication Date:
Data Source:
PubMed
Source Link:
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Record Created: