[AI-assisted radiology in the management of respiratory infections].
Authors
De Pasquale N,Rotzinger D,Pozzessere C,Boillat-Blanco N,Suttels V
Affiliations (3)
Affiliations (3)
- Service des maladies infectieuses, Centre hospitalier universitaire vaudois et Université de Lausanne, 1011 Lausanne.
- Service de radiologie, Centre hospitalier universitaire vaudois et Université de Lausanne, 1011 Lausanne.
- LiGHT Laboratory, École polytechnique fédérale de Lausanne, 1015 Lausanne.
Abstract
Respiratory infections are among the leading causes of consultation in primary care and emergency settings and account for substantial healthcare resource use. Their management relies heavily on chest imaging, particularly radiography and, more recently, lung ultrasound. Artificial intelligence (AI) applied to these modalities offers new opportunities to improve anomaly detection, reduce interobserver variability, and support clinical decision-making. This article summarizes recent evidence on the contribution of AI in thoracic imaging for the diagnosis of respiratory infections, particularly pneumonia and tuberculosis, while highlighting current limitations and challenges related to validation and implementation.
Topics
Respiratory Tract InfectionsArtificial IntelligenceJournal ArticleReviewEnglish Abstract