ArticleJournal of perinatology : official journal of the California Perinatal Association2025
Glottic opening detection using deep learning for neonatal intubation with video laryngoscopy.
Article in Journal of perinatology : official journal of the California Perinatal Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of artificial intelligence in early childhood health management: a systematic review from fetal to pediatric periods.Frontiers in pediatrics · 2025Pooled it
- Airway coach project: development of a machine learning-based model using clinical and ultrasound parameters to support videolaryngoscopy strategy.BMC anesthesiology · 2026Observational
- Comparing artificial intelligence and healthcare professional performance in surgical and interventional video analysis: a systematic review and meta-analysis.NPJ digital medicine · 2026Article
- Deep learning to assess laryngoscope insertion depth during neonatal intubation with video laryngoscopy.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- Application of an artificial intelligence-based airway identification system in tracheal intubation.BMC anesthesiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
objectiveThis study aimed to develop an artificial intelligence (AI) method to augment video laryngoscopy (VL) by automating the detection of the glottic opening in neonates, as a step toward future studies on improving intubation outcomes. STUDY
designA deep learning model, YOLOv8, was trained on 1623 video frames from 84 neonatal intubations to detect the glottic opening and evaluated using 14-fold cross-validation on metrics like precision and recall. Additionally, it was compared with 25 medical providers of varied intubation experience to assess its relative performance.
resultsThe model demonstrated a precision of 80.8% and a recall of 75.3% in identifying the glottic opening, detecting it 0.31 s faster than the average medical provider. It performed comparably or better than novice and intermediate providers, and slightly slower than experts.
conclusionAI-powered tools can aid VL by providing real-time guidance, potentially enhancing neonatal intubation safety and efficiency for less experienced users.
Indexed as
Identifiers
39537817What 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.