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Using AI to Detect Pain through Facial Expressions: A Review.
De Sario, Gioacchino D; Haider, Clifton R; Maita, Karla C; Torres-Guzman, Ricardo A; Emam, Omar S; Avila, Francisco R; Garcia, John P; Borna, Sahar; McLeod, Christopher J; Bruce, Charles J; Carter, Rickey E; Forte, Antonio J.
Afiliação
  • De Sario GD; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Haider CR; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55902, USA.
  • Maita KC; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Torres-Guzman RA; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Emam OS; Division of AI in Health Sciences, University of Louisville, Louisville, KY 40292, USA.
  • Avila FR; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Garcia JP; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Borna S; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
  • McLeod CJ; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Bruce CJ; Department of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Carter RE; Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL 32224, USA.
  • Forte AJ; Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
Bioengineering (Basel) ; 10(5)2023 May 02.
Article em En | MEDLINE | ID: mdl-37237618
ABSTRACT
Pain assessment is a complex task largely dependent on the patient's self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Ethics Idioma: En Revista: Bioengineering (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Ethics Idioma: En Revista: Bioengineering (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos
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