ReviewBioengineering (Basel, Switzerland)2023
Using AI to Detect Pain through Facial Expressions: A Review.
Review in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Robot-Assisted Oral Examination: Challenges and Innovations.International dental journal · 2026Pooled it
- Application of AI in Multilevel Pain Assessment Using Facial Images: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Automated Vision-Based Sensing of Paediatric Pain Using 2D-Facial Landmark Trajectories Derived from 3D Geometric Normalisation and a Spatial-Temporal Attention Long Short-Term Memory (STA-LSTM) Network.Sensors (Basel, Switzerland) · 2026Article
- Pain in Alzheimer's Disease: Disrupted Multilevel Integration of Nociception, Affective Processing and Clinical Expression Across Clinical and Preclinical Evidence.Life (Basel, Switzerland) · 2026Review
- Connectivity-Based Pain Recognition from fNIRS: Parsimonious Subject-Independent Classification.Sensors (Basel, Switzerland) · 2026Article
- Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients.Nursing in critical care · 2026Article
- Deep Learning-Based Instance Appraisable Model (EDi Pain) for Pain Estimation via Facial Videos: A Retrospective Analysis and a Prospective Emergency Department Study.Journal of imaging informatics in medicine · 2026Article
- Comparing the performance of deep learning video-based models and trained veterinarians in cattle pain assessment.Scientific reports · 2026Article
- Facial Expressions as a Nexus for Health Assessment.Bioengineering (Basel, Switzerland) · 2026Review
- Automated Facial Pain Assessment Using Dual-Attention CNN with Clinically Calibrated High-Reliability and Reproducibility Framework.Biomimetics (Basel, Switzerland) · 2026Article
- Rethinking Pain Assessment: Subjective Scales, Biomarkers, and Multimodal Integration.Journal of pain research · 2026Review
- Prediction of postoperative nausea and vomiting in patients undergoing sedated gastrointestinal endoscopy based on machine learning.Annals of medicine · 2025Article
- Objective monitoring of acute pain and nociception in anaesthesia and intensive care: evidence and applications.Anaesthesiology intensive therapy · 2025Review
- A Public Health Approach to Automated Pain Intensity Recognition in Chest Pain Patients via Facial Expression Analysis for Emergency Care Prioritization.Diagnostics (Basel, Switzerland) · 2025Article
- Emoface: AI-assisted diagnostic model for differentiating major depressive disorder and bipolar disorder via facial biomarkers.Npj mental health research · 2025Article
- Identification of technology-based models and efficacy of digital-based pain facial expression assessment tools among children: a systematic review.BMC nursing · 2025Article
- Comparison between AI and human expert performance in acute pain assessment in sheep.Scientific reports · 2025Article
- The Potential for High-Priority Care Based on Pain Through Facial Expression Detection with Patients Experiencing Chest Pain.Diagnostics (Basel, Switzerland) · 2024Article
- Using facial reaction analysis and machine learning to objectively assess the taste of medicines in children.PLOS digital health · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
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What OpenQuestion holds
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.