This paper is in the following e-collection/theme issue:

Digital Pain Assessment and Management (232) Machine Learning (2076) Artificial Intelligence (2129) Pain in Children and Adolescents (58) Mobile Health (mhealth) (3464)

Published on in Vol 25 (2023)

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

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

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

Authors of this article:

Jeffery David Hughes1 Author Orcid Image ;   Paola Chivers2, 3 Author Orcid Image ;   Kreshnik Hoti4 Author Orcid Image
Article Authors Cited by (21) Tweetations (3) Metrics

Journals

  1. Huo J, Yu Y, Lin W, Hu A, Wu C. Application of AI in Multilevel Pain Assessment Using Facial Images: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2024;26:e51250 View
  2. Yoshimi Y, Matsuura T, Miyazato K, Takahashi S, Tanaka N, Morinaga H, Hayata A, Onishi M, Nagano Y, Ohnishi H. Availability of Observational Pain Assessment Tools in Hospitalized Patients with Osteoporotic Vertebral Fractures. Medicina 2024;60(8):1217 View
  3. Srivastava S, Khanna V. Management of Pain in Patients with Osteoporotic Fractures. International Journal of Innovative Science and Research Technology (IJISRT) 2024:1838 View
  4. Cascella M, Leoni M, Shariff M, Varrassi G. Artificial Intelligence-Driven Diagnostic Processes and Comprehensive Multimodal Models in Pain Medicine. Journal of Personalized Medicine 2024;14(9):983 View
  5. Yang N, Zhuang Y, Jiang H, Fang Y, Li J, Zhu L, Zhao W, Shi T. Developing and Validating a Multimodal Dataset for Neonatal Pain Assessment to Improve AI Algorithms With Clinical Data. Advances in Neonatal Care 2024;24(6):578 View
  6. Karkoutly M, Alatassi L, Azrak L, Bshara N. Efficacy of topical anesthetics of lidocaine, benzocaine, and EMLA in reducing pain during inferior alveolar nerve block in schoolchildren: a randomized controlled trial. BDJ Open 2024;10(1) View
  7. Sada F, Chivers P, Cecelia S, Statovci S, Ukperaj K, Hughes J, Hoti K. Parental Assessment of Postsurgical Pain in Infants at Home Using Artificial Intelligence–Enabled and Observer-Based Tools: Construct Validity and Clinical Utility Evaluation Study. JMIR Pediatrics and Parenting 2024;7:e64669 View
  8. Feighelstein M, Luna S, Silva N, Trindade P, Shimshoni I, van der Linden D, Zamansky A. Comparison between AI and human expert performance in acute pain assessment in sheep. Scientific Reports 2025;15(1) View
  9. Yiğit D, Açıkgöz A. Evaluation of Nurse Academicians’ Knowledge, Attitudes/Behaviours, and Anxiety Levels Regarding Artificial Intelligence Applications. Genel Tıp Dergisi 2024;34(6):875 View
  10. Zhang L, Zhu T, Zhang Y. A Deep Learning Approach for Infant Pain Assessment Using Facial Expressions Through Convolutional Neural Network. CIN: Computers, Informatics, Nursing 2025;43(7) View
  11. LaRosa J, Kudchadkar S. Personalizing ICU liberation for critically Ill children: shaping the future of the ABCDEF bundle. Current Opinion in Pediatrics 2025;37(3):216 View
  12. Färnqvist K, Olsson E, Garratt A, Paraskevas T, Soll R, Bruschettini M, Persad E. Clinical rating scales for assessing pain in newborn infants. Cochrane Database of Systematic Reviews 2025;2025(4) View
  13. Ofosu-Dwamena S, Maree C, Rossouw S, Bhana-Pema V. Caregivers’ role regarding managing postoperative pain of hospitalised children (0–3 years). Health SA Gesondheid 2025;30(0) View
  14. Tuppal C, Ninobla M, Loresco R, Cabradilla M, Tuppal S, Pellacœur L, Roa M, Chan J, Panes I, Ferares A, Caspillo I. Looking into the Future of ChatGPT and Its Cultural Consideration from Filipino Nurse Scientists’ Perspectives: A Narrative-Focused Group Discussion. Creative Nursing 2025;31(3):318 View
  15. Ramdhanie G, Wanda D, Agustini N, Abuzairi T. Identification of technology-based models and efficacy of digital-based pain facial expression assessment tools among children: a systematic review. BMC Nursing 2025;24(1) View
  16. Park T, Lee I, Lee S, Kong S. Artificial intelligence in pediatric healthcare: current applications, potential, and implementation considerations. Clinical and Experimental Pediatrics 2025;68(9):641 View
  17. Assiry A, Alrehaili R, Mahnashi A, Alkam H, Mahdi R, Hakami R, Alshammakhy R, Almallahi W, Alhawsah Y, Khalil A. How Is Artificial Intelligence Transforming the Intersection of Pediatric and Special Care Dentistry? A Scoping Review of Current Applications and Ethical Considerations. Prosthesis 2025;7(5):119 View
  18. Çubukcu E, Kahraman A. Pediatri hastalarının ağrı değerlendirmesinde hemşirelerin yapay zekâ ve makine öğrenimi uygulamaları. Journal of Infant, Child and Adolescent Health 2025;5(2):135 View
  19. Mohabir V, Lalloo C, Briggs A, Eccleston C, Hess C, Pham Q, Slater H, Velmovitsky P, Stinson J. The transformative potential of digital therapeutics in pediatrics. Pain 2025;166(11S):S121 View

Books/Policy Documents

  1. Cascella M. Exploring AI in Pain Research and Management. View

Conference Proceedings

  1. Hapsari D, Nataliani Y, Sembiring I, Wahyono T. 2024 International Conference on Smart Computing, IoT and Machine Learning (SIML). Smart Caregiving Support Cloud Integration Systems View