Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study

Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study

Abstract Background In Sweden with about 10 million inhabitants, there are about one million primary ambulance missions every year. Among them, around 10% are assessed by Emergency Medical Service (EMS) clinicians with the primary symptom of dyspnoea. The risk of death among these patients has been...

Disgrifiad llawn

Manylion Llyfryddiaeth
Prif Awduron: Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson
Fformat: Erthygl
Iaith:English
Cyhoeddwyd: BMC 2025-01-01
Cyfres:BMC Emergency Medicine
Pynciau:
Dyspnoea
Serious adverse event
Prehospital
Ambulance
Emergency medical services
Machine learning
Mynediad Ar-lein:https://doi.org/10.1186/s12873-024-01166-9

Rhyngrwyd

https://doi.org/10.1186/s12873-024-01166-9

Eitemau Tebyg