Published on in Vol 24, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40387, first published .
Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial

Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial

Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial

Joël Belmin   1, 2 , MD, PhD ;   Patrick Villani   3, 4 , MD, PhD ;   Mathias Gay   5 , PhD ;   Stéphane Fabries   6 , MS ;   Charlotte Havreng-Théry   1, 7 , PhD ;   Stéphanie Malvoisin   8 , MD ;   Fabrice Denis   9 , MD, PhD ;   Jacques-Henri Veyron   7 , MS

1 Laboratoire Informatique Médicale et Ingénierie des Connaissances en eSanté (UMRS 1142), Institut National de la Santé et de la Recherche Médicale and Sorbonne Université, Paris, France

2 Hôpital Charles Foix, Assistance Publique-Hôpitaux de Paris, Ivry-sur-Seine, France

3 Unité de Médecine Interne, Gériatrie et Thérapeutique, Assistance Publique-Hôpitaux de Marseille, Marseille, France

4 Etablissement Français du Sang, Anthropologie bio-culturelle, Droit, Ethique et Santé, Centre National de la Recherche Scientifique, Université Aix-Marseille, Marseille, France

5 Communauté professionnelle de santé Itinéraire Santé, Marseille, France

6 Intervenants Libéraux et Hospitaliers Unis pour le Patient, Marseille, France

7 Presage, Paris, France

8 Centre hospitalo-universitaire La Réunion, Saint-Pierre, French Southern Territories

9 Institut Inter-Régional de Cancérologie Jean Bernard, Le Mans, France

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