Evidence map›Paper›PMID 38062194›Full record

ArticleScientific reports2023

Fully automated deep learning models with smartphone applicability for prediction of pain using the Feline Grimace Scale.

P V Steagall, B P Monteiro, S Marangoni, M Moussa, M Sautié

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Review
  2. Review
  3. CowPainCheck: AI-based facial expression analysis for dairy cow welfare.Journal of animal science and technology · 2026
    Review
  4. Article
  5. Seen but overlooked: animals as stakeholders in AI ethics discourses.Animal frontiers : the review magazine of animal agriculture · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Video-based compilation of acute pain behaviours in cats.Journal of feline medicine and surgery · 2024
    Article
  12. Review
  13. Feline Aortic Thromboembolism: Recent advances and future prospects.Journal of feline medicine and surgery · 2024
    Review
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

P V SteagallDepartment of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada. pmortens@cityu.edu.hk.
B P MonteiroDepartment of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada.
S MarangoniDepartment of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada.
M MoussaPlateforme IA-Agrosanté, Université de Montréal, Saint-Hyacinthe, QC, Canada.
M SautiéPlateforme IA-Agrosanté, Université de Montréal, Saint-Hyacinthe, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study used deep neural networks and machine learning models to predict facial landmark positions and pain scores using the Feline Grimace Scale

Indexed as

Acute PainDeep LearningAnimalsCatsMachine LearningNeural Networks, ComputerSmartphone

Identifiers

PMID38062194
PMCPMC10703818

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.