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Profil bibliographique

Annette Kjær Ersbøll

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

531Publications signalées
12522Citations signalées
4Affiliations récentes

Les institutions déclarées

Les domaines associés

Cardiac Arrest and ResuscitationAnimal Behavior and Welfare StudiesAnimal Disease Management and EpidemiologyHealth disparities and outcomesTrauma and Emergency Care Studies

Les publications récentes

Accès ouvert 2026 article OpenAlex

Frequent Callers to Emergency Medical Services: an observational cohort study from Region Zealand, Denmark (2018–2025)

Amalie Elisabeth Thiele-Nygaard, Thea Palsgaard Møller, Stig Nikolaj Fasmer Blomberg, Lars Bredevang Andersen et autres

Frequent callers to Emergency Medical Services represent a small group of citizens who account for a substantial number of calls. Despite their impact, little is known about their characteristics and patterns of EMS use. This study aimed to examine frequency, dispatch outcomes, …

dk (code pays fourni par la source)

0 citations BMC Emergency Medicine
Accès ouvert 2026 article OpenAlex

Urban heat vulnerability in a warming climate in Denmark: Projected temperature-related mortality for Copenhagen and the remaining areas

Stine Kloster, Karsten Arnbjerg‐Nielsen, Hjalte Jomo Danielsen Sørup, Mark Payne et autres

Objective We estimated future cold- and heat-related mortality for Copenhagen and remaining areas in Denmark under different warming scenarios. Methods We used nationwide historical and projected data on temperature, mortality, and population size. For 2000–2019, daily deaths were modelled using a Poisson …

dk (code pays fourni par la source)

0 citations Urban Climate
Accès ouvert 2026 article OpenAlex

Assessing different machine learning algorithms to identify traumatic cardiac arrest: proof of concept

Signe Amalie Wolthers, Mehdi Parviz, Caroline Kamuk Ostenfeldt, Annette Kjær Ersbøll et autres

OBJECTIVE: Traumatic cardiac arrest differs from non-traumatic regarding epidemiology. This study evaluated five machine learning classifiers' ability to identify traumatic cardiac arrest in the Danish Cardiac Arrest Registry, which currently relies on manual review. METHODS: This retrospective study employed split sampling to …

dk (code pays fourni par la source)

0 citations Annals of Epidemiology

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