Evaluating neonatal pain via fusing vision transformer and concept-cognitive computing.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
31 Oct 2024
Historique:
received: 15 08 2024
accepted: 23 10 2024
medline: 1 11 2024
pubmed: 1 11 2024
entrez: 1 11 2024
Statut: epublish

Résumé

In clinical nursing, neonatal pain assessment is a challenging task for preventing and controlling the impact of pain on neonatal development. To reduce the adverse effects of repetitive painful treatments during hospitalization on newborns, we propose a novel method (namely pain concept-cognitive computing model, PainC3M) for evaluating facial pain in newborns. In the fusion system, we first improve the attention mechanism of vision transformer by revising the node encoding way, considering the spatial structure, edge and centrality of nodes, and then use its corresponding encoder as a feature extractor to comprehensively extract image features. Second, we introduce a concept-cognitive computing model as a classifier to evaluate the level of pain. Finally, we evaluate our PainC3M on various open pain data sets and a real clinical pain data stream, and the experimental results demonstrate that our PainC3M is very effective for dynamic classification and superior to other comparative models. It also provides a good approach for pain assessment of individuals with aphasia (or dementia).

Identifiants

pubmed: 39482345
doi: 10.1038/s41598-024-77521-4
pii: 10.1038/s41598-024-77521-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

26201

Subventions

Organisme : the Hunan Provincial Natural Science Foundation of China
ID : (No. 2024JJ7374, No. 2023JJ50456, No. 2024JJ7383)
Organisme : the Hunan Provincial Natural Science Foundation of China
ID : (No. 2024JJ7374, No. 2023JJ50456, No. 2024JJ7383)
Organisme : the Scientific Research Projects of the Hunan Provincial Department of Education
ID : (No. 21A0488, No. 22A0547, No. 23B0719)
Organisme : the Scientific Research Projects of the Hunan Provincial Department of Education
ID : (No. 21A0488, No. 22A0547, No. 23B0719)

Informations de copyright

© 2024. The Author(s).

Références

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Auteurs

Jing Lin (J)

School of Computer and Artificial Intelligence, Huaihua University, Huaihua, 418000, China. linjing@hhtc.edu.cn.

Liang Zhang (L)

School of Computer and Artificial Intelligence, Huaihua University, Huaihua, 418000, China.

Jianhua Xia (J)

School of Computer and Artificial Intelligence, Huaihua University, Huaihua, 418000, China.

Yuping Zhang (Y)

Obstetrical Department of Huaihua Second People's Hospital, Huaihua, 418000, China.

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