ArticlePaediatric & neonatal pain2025
Objective Detection of Newborn Infant Acute Procedural Pain Using EEG and Machine Learning Algorithms.
Article in Paediatric & neonatal pain, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in pediatric pain: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- Electroencephalography during acute painful procedures in neonates: a scoping review.Pain reports · 2026Review
- Application of Intelligent Neonatal Pain Assessment Tools Based on Multimodal Data Fusion: A Systematic Review.Journal of pain research · 2026Review
- Automated Deep Learning Approach for Post-Operative Neonatal Pain Detection and Prediction through Physiological Signals.Proceedings. IEEE International Symposium on Computer-Based Medical Systems · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Observer-dependent infant pain scales have limitations including discontinuous assessments and the lack of healthcare professionals' availability. We hypothesized that applying agnostic machine learning approaches to neonatal electroencephalographic (EEG) analysis may reveal features of the infant response to acute pain. EEG was recorded from 30 neonates undergoing acutely painful procedures (18 males, 34.0-41.7 weeks gestation at birth). EEG recordings were randomly assigned to training (
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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.