ArticleProceedings : Annual International Computer Software and Applications Conference. COMPSAC2021
Pain Action Unit Detection in Critically Ill Patients.
Article in Proceedings : Annual International Computer Software and Applications Conference. COMPSAC, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Pain assessment tools in adults with communication disorders: systematic review and meta-analysis.BMC neurology · 2024Pooled it
- Review
- Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients.Nursing in critical care · 2026Article
- An exploratory study of headache pain intensity using facial expressions and APEX frames.NPJ digital medicine · 2026Article
- Identification of technology-based models and efficacy of digital-based pain facial expression assessment tools among children: a systematic review.BMC nursing · 2025Article
- A Weighted Facial Expression Analysis for Pain Level Estimation.Journal of imaging · 2025Article
- Article
- FaceFinder: A machine learning tool for identification of facial images from heterogenous datasets.AJO international · 2024Article
- Transformers and large language models in healthcare: A review.Artificial intelligence in medicine · 2024Review
- Diurnal Pain Classification in Critically Ill Patients using Machine Learning on Accelerometry and Analgesic Data.IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine · 2023Article
- Automated facial recognition system using deep learning for pain assessment in adults with cerebral palsy.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Existing pain assessment methods in the intensive care unit rely on patient self-report or visual observation by nurses. Patient self-report is subjective and can suffer from poor recall. In the case of non-verbal patients, behavioral pain assessment methods provide limited granularity, are subjective, and put additional burden on already overworked staff. Previous studies have shown the feasibility of autonomous pain expression assessment by detecting Facial Action Units (AUs). However, previous approaches for detecting facial pain AUs are historically limited to controlled environments. In this study, for the first time, we collected and annotated a pain-related AU dataset,
Indexed as
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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.