Evidence map›Paper›PMID 35547946›Full record

ReviewPaediatric & neonatal pain2021

Future roles of artificial intelligence in early pain management of newborns.

Md Sirajus Salekin, Peter R Mouton, Ghada Zamzmi, Raj Patel, Dmitry Goldgof, Marcia Kneusel, Sammie L Elkins, Eileen Murray, Mary E Coughlin, Denise Maguire and 2 more

Open access · goldAbstract readReview
In one paragraph

Review in Paediatric & neonatal pain, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.3field-weighted citation impact, top 4% of its field
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

16 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. [Research progress in artificial intelligence for the diagnosis and management of diseases in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026
    Review
  5. Review
  6. Review
  7. Few-Shot Prompting with Vision Language Model for Pain Classification in Infant Cry Sounds.Proceedings. IEEE International Symposium on Computer-Based Medical Systems · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Biomarkers for assessing pain and pain relief in the neonatal intensive care unit.Frontiers in pain research (Lausanne, Switzerland) · 2024
    Review
  12. Article
  13. Attentional Generative Multimodal Network for Neonatal Postoperative Pain Estimation.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022
    Article
  14. Review
  15. Review
  16. 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

12 authors at 1 institution in 1 country.

Md Sirajus SalekinComputer Science and Engineering Department University of South Florida Tampa FL USA.
Peter R MoutonSRC Biosciences Tampa FL USA.
Ghada ZamzmiComputer Science and Engineering Department University of South Florida Tampa FL USA.
Raj PatelMuma College of Business University of South Florida Tampa FL USA.
Dmitry GoldgofComputer Science and Engineering Department University of South Florida Tampa FL USA.
Marcia KneuselCollege of Medicine Pediatrics USF Health University of South Florida Tampa FL USA.
Sammie L ElkinsSRC Biosciences Tampa FL USA.
Eileen MurraySRC Biosciences Tampa FL USA.
Mary E CoughlinCaring Essentials Collaborative, LLC Boston MA USA.
Denise MaguireCollege of Nursing USF Health University of South Florida Tampa FL USA.ORCID https://orcid.org/0000-0003-0670-196X
Thao HoCollege of Medicine Pediatrics USF Health University of South Florida Tampa FL USA.
Yu SunComputer Science and Engineering Department University of South Florida Tampa FL USA.
University of South Florida · US

Funding

A Multimodal Approach for Monitoring Prolonged Acute Pain in NeonatesR21NR018756 · NINR · UNIVERSITY OF SOUTH FLORIDA · PI SUN, YU · 2020 to 2021
$401k
An AI-based Multimodal Approach to Predict Pain in Postnatal Care ScenariosR41HD109086 · NICHD · STEREOLOGY RESOURCE CENTER, INC. · PI MOUTON, PETER RANDOLPH, SUN, YU · 2022 to 2022
$315k
NICHD NIH HHS R41 HD109086NINR NIH HHS R21 NR018756
6 · The paper itself

Abstract

The advent of increasingly sophisticated medical technology, surgical interventions, and supportive healthcare measures is raising survival probabilities for babies born premature and/or with life-threatening health conditions. In the United States, this trend is associated with greater numbers of neonatal surgeries and higher admission rates into neonatal intensive care units (NICU) for newborns at all birth weights. Following surgery, current pain management in NICU relies primarily on narcotics (opioids) such as morphine and fentanyl (about 100 times more potent than morphine) that lead to a number of complications, including prolonged stays in NICU for opioid withdrawal. In this paper, we review current practices and challenges for pain assessment and treatment in NICU and outline ongoing efforts using Artificial Intelligence (AI) to support pain- and opioid-sparing approaches for newborns in the future. A major focus for these next-generation approaches to NICU-based pain management is proactive pain mitigation (avoidance) aimed at preventing harm to neonates from

Indexed as

neonatal intensive care unitneonatal pain assessmentneonatal pain predictionnewborn pain managementopioid‐based pain management

Identifiers

PMID35547946
PMCPMC8975206
OpenAlexW3187209091

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.