ArticleJournal of clinical medicine2018
Automatic Infants' Pain Assessment by Dynamic Facial Representation: Effects of Profile View, Gestational Age, Gender, and Race.
Article in Journal of clinical medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Artificial intelligence in pediatric pain: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- MSAFNet: A multi-scale attention fusion network for automated neonatal pain facial expression recognition with clinical validation.Scientific reports · 2026Article
- Automated detection of mouth opening in newborn infants.Behavior research methods · 2025Article
- Personalizing ICU liberation for critically Ill children: shaping the future of the ABCDEF bundle.Current opinion in pediatrics · 2025Review
- Construction and validation of a pain facial expressions dataset for critically ill children.Scientific reports · 2025Article
- How facial expressions reveal acute pain in domestic animals with facial pain scales as a diagnostic tool.Frontiers in veterinary science · 2025Review
- Facial thermal response to non-painful stressor in premature and term neonates.Pediatric research · 2023Article
- Multimodal pain assessment improves discrimination between noxious and non-noxious stimuli in infants.Paediatric & neonatal pain · 2019Article
- Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units.Jornal de pediatriaReview
- Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infants' early exposure to painful procedures can have negative short and long-term effects on cognitive, neurological, and brain development. However, infants cannot express their subjective pain experience, as they do not communicate in any language. Facial expression is the most specific pain indicator, which has been effectively employed for automatic pain recognition. In this paper, dynamic pain facial expression representation and fusion scheme for automatic pain assessment in infants is proposed by combining temporal appearance facial features and temporal geometric facial features. We investigate the effects of various factors that influence pain reactivity in infants, such as individual variables of gestational age, gender, and race. Different automatic infant pain assessment models are constructed, depending on influence factors as well as facial profile view, which affect the model ability of pain recognition. It can be concluded that the profile-based infant pain assessment is feasible, as its performance is almost as good as that of the whole face. Moreover, gestational age is the most influencing factor for pain assessment, and it is necessary to construct specific models depending on it. This is mainly because of a lack of behavioral communication ability in infants with low gestational age, due to limited neurological development. To our best knowledge, this is the first study investigating infants' pain recognition, highlighting profile facial views and various individual variables.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.