Statistics for "Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden"

Record

Title: Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden
Type: Journal Article
Publ. year: 2025
Author/s: Tolestam Heyman, Ellen; Ashfaq, Awais; Ekelund, Ulf; Ohlsson, Mattias et al.
Department/s: Emergency medicine; Medicine/Emergency Medicine, Lund; EpiHealth: Epidemiology for Health; Computational Science for Health and Environment; LU Profile Area: Natural and Artificial Cognition; Centre for Environmental and Climate Science (CEC); eSSENCE: The e-Science Collaboration; Artificial Intelligence in CardioThoracic Sciences (AICTS); LU Profile Area: Nature-based future solutions; EPI@BIO; Surgery and public health; Centre for Economic Demography; Division of Occupational and Environmental Medicine, Lund University; Cardiovascular Research - Hypertension
In LUP since: 2025-05-29

Downloads

Total	This Year	This Month
15	15	2

Downloads per country
Sweden	10 (71%)
United States of America	4 (29%)