Explainable automated pain recognition in cats

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversity of Haifa-
Autor(es): dc.contributorIsrael Institute of Technology-
Autor(es): dc.contributorUniversity of Veterinary Medicine Hannover-
Autor(es): dc.contributorNational Cat Centre-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of Lincoln-
Autor(es): dc.creatorFeighelstein, Marcelo-
Autor(es): dc.creatorHenze, Lea-
Autor(es): dc.creatorMeller, Sebastian-
Autor(es): dc.creatorShimshoni, Ilan-
Autor(es): dc.creatorHermoni, Ben-
Autor(es): dc.creatorBerko, Michael-
Autor(es): dc.creatorTwele, Friederike-
Autor(es): dc.creatorSchütter, Alexandra-
Autor(es): dc.creatorDorn, Nora-
Autor(es): dc.creatorKästner, Sabine-
Autor(es): dc.creatorFinka, Lauren-
Autor(es): dc.creatorLuna, Stelio P. L.-
Autor(es): dc.creatorMills, Daniel S.-
Autor(es): dc.creatorVolk, Holger A.-
Autor(es): dc.creatorZamansky, Anna-
Data de aceite: dc.date.accessioned2025-08-21T22:42:50Z-
Data de disponibilização: dc.date.available2025-08-21T22:42:50Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-11-30-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1038/s41598-023-35846-6-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/247508-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/247508-
Descrição: dc.descriptionManual tools for pain assessment from facial expressions have been suggested and validated for several animal species. However, facial expression analysis performed by humans is prone to subjectivity and bias, and in many cases also requires special expertise and training. This has led to an increasing body of work on automated pain recognition, which has been addressed for several species, including cats. Even for experts, cats are a notoriously challenging species for pain assessment. A previous study compared two approaches to automated ‘pain’/‘no pain’ classification from cat facial images: a deep learning approach, and an approach based on manually annotated geometric landmarks, reaching comparable accuracy results. However, the study included a very homogeneous dataset of cats and thus further research to study generalizability of pain recognition to more realistic settings is required. This study addresses the question of whether AI models can classify ‘pain’/‘no pain’ in cats in a more realistic (multi-breed, multi-sex) setting using a more heterogeneous and thus potentially ‘noisy’ dataset of 84 client-owned cats. Cats were a convenience sample presented to the Department of Small Animal Medicine and Surgery of the University of Veterinary Medicine Hannover and included individuals of different breeds, ages, sex, and with varying medical conditions/medical histories. Cats were scored by veterinary experts using the Glasgow composite measure pain scale in combination with the well-documented and comprehensive clinical history of those patients; the scoring was then used for training AI models using two different approaches. We show that in this context the landmark-based approach performs better, reaching accuracy above 77% in pain detection as opposed to only above 65% reached by the deep learning approach. Furthermore, we investigated the explainability of such machine recognition in terms of identifying facial features that are important for the machine, revealing that the region of nose and mouth seems more important for machine pain classification, while the region of ears is less important, with these findings being consistent across the models and techniques studied here.-
Descrição: dc.descriptionInformation Systems Department University of Haifa-
Descrição: dc.descriptionFaculty of Electrical Engineering Technion Israel Institute of Technology-
Descrição: dc.descriptionDepartment of Small Animal Medicine and Surgery University of Veterinary Medicine Hannover-
Descrição: dc.descriptionCats Protection National Cat Centre, Sussex-
Descrição: dc.descriptionSchool of Veterinary Medicine and Animal Science São Paulo State University (Unesp)-
Descrição: dc.descriptionSchool of Life Sciences Joseph Bank Laboratories University of Lincoln-
Descrição: dc.descriptionSchool of Veterinary Medicine and Animal Science São Paulo State University (Unesp)-
Idioma: dc.languageen-
Relação: dc.relationScientific Reports-
???dc.source???: dc.sourceScopus-
Título: dc.titleExplainable automated pain recognition in cats-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.