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Artificial intelligence in public health : lessons from the European public health conference

Title: Artificial intelligence in public health : lessons from the European public health conference
Authors: Panteli, Dimitra; Buttigieg, Stefan; Keyrellous, Adib; Ladewig, Katharina; Azzopardi Muscat, Natasha; McKee, Martin
Publisher Information: European Observatory on Health Systems and Policies
Publication Year: 2024
Collection: University of Malta: OAR@UM / L-Università ta' Malta
Subject Terms: Artificial intelligence -- Medical applications -- European Union countries; Artificial intelligence -- Medical applications -- Congresses; European Union. Artificial Intelligence Act; Public health -- Technological innovations
Description: Artificial intelligence (AI) holds great promise for advancing public health functions. This article, drawing on discussions from Plenary 1 at the European Public Health Conference 2024, considers some ways in which AI is already used in public health, including for health promotion, surveillance and protection, population health assessment, disease and injury prevention, emergency prediction, preparedness and response, and resource optimisation. It also explores what actions need to be taken in the future to help ensure AI is meaningfully embedded in public health practice, and to overcome key challenges such as ensuring equity, avoiding biases, maintaining trust, and safeguarding privacy. ; peer-reviewed
Document Type: article in journal/newspaper
Language: English
ISSN: 2958096X
Relation: https://www.um.edu.mt/library/oar/handle/123456789/133192
Availability: https://www.um.edu.mt/library/oar/handle/123456789/133192
Rights: info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.
Accession Number: edsbas.52B82F3C
Database: BASE