The Clinical Suitability of an Artificial Intelligence-Enabled Pain Assessment Tool for Use in Infants: Feasibility and Usability Evaluation Study.

Hughes, Jeffery David; Chivers, Paola; Hoti, Kreshnik

Hughes, Jeffery David; Chivers, Paola; Hoti, Kreshnik.

Affiliation

Hughes JD; Curtin Medical School, Curtin University, Perth, Australia.
Chivers P; Institute for Health Research, The University of Notre Dame Australia, Fremantle, Australia.
Hoti K; School of Medical and Health Sciences, Edith Cowan University, Perth, Australia.

J Med Internet Res ; 25: e41992, 2023 02 13.

Article in En | MEDLINE | ID: mdl-36780223

Subject(s)

Artificial Intelligence; Pain, Procedural; Humans; Infant; Pain, Procedural/diagnosis; Feasibility Studies; Pain Measurement; Pain/diagnosis

Key words

PainChek Infant; accuracy; artificial intelligence; assessment; babies; baby; clinical utility; detection; facial; immunization; infant; machine learning; model; newborn; pain; pain assessment; precision; sensitivity; specificity

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Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Pain, Procedural Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans / Infant Language: En Year: 2023 Type: Article

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