Expert consensus on feasibility and application of automatic pain assessment in routine clinical use

Expert consensus on feasibility and application of automatic pain assessment in routine clinical use

Abstract Background Pain is often difficult to assess, particularly in non-communicative patients. While artificial intelligence (AI)-based objective Automatic Pain Assessment (APA) systems are a promising solution, their clinical implementation raises essential questions, primarily regarding clinic...

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Main Authors: Marco Cascella, Alfonso Maria Ponsiglione, Vittorio Santoriello, Maria Romano, Valentina Cerrone, Dalila Esposito, Mario Montedoro, Roberta Pellecchia, Gennaro Savoia, Giuliano Lo Bianco, Massimo Innamorato, Silvia Natoli, Jonathan Montomoli, Federico Semeraro, Elena Giovanna Bignami, Valentina Bellini, Matteo Luigi Giuseppe Leoni, Felice Occhigrossi, Alessandro Vittori, Maria Caterina Pace, Pasquale Buonanno, Mauro Forte, Elisabetta Chinè, Roberta Carpenedo, Alessandro De Cassai, Alfonso Papa, Maurizio Marchesini, Gaetano Terranova, Fabrizio Micheli, Laura Demartini, Franco Marinangeli, William Raffaeli, Flaminia Coluzzi, Andrea Tinnirello, Roberto Arcioni, Angelo Marra, Mohammed Naveed Shariff, Federica Monaco, Gabriele Finco, Alessia Bramanti, Ornella Piazza
Format: Article
Language:English
Published: BMC 2025-06-01
Series:Journal of Anesthesia, Analgesia and Critical Care
Subjects:
Artificial intelligence
Automatic pain assessment
Pain
Pediatric pain
Opioid
Pain therapy
Online Access:https://doi.org/10.1186/s44158-025-00249-8
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https://doi.org/10.1186/s44158-025-00249-8

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