Evidence map›Paper›PMID 38328019›Full record

ReviewJournal of pain research2024

Artificial Intelligence and Pain Medicine: An Introduction.

Jonathan M Hagedorn, Tony K George, Rohit Aiyer, Keith Schmidt, John Halamka, Ryan S D'Souza

Abstract readReview
In one paragraph

Review in Journal of pain research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
–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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025
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  9. General Innovations in Pain Management.Journal of clinical medicine · 2025
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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

6 authors.

Jonathan M HagedornDepartment of Anesthesiology and Perioperative Medicine, Division of Pain Medicine, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0003-1039-8166
Tony K GeorgeDepartment of Physical Medicine and Rehabilitation, University Orthopedic Associates, Somerset, NJ, USA.
Rohit AiyerIntegrative Sports & Spine, Long Beach, CA, USA.
Keith SchmidtComprehensive Pain Management Program, St. Alexius Medical Center, Hoffman Estates, IL, USA.
John HalamkaMayo Clinic Platform, Mayo Clinic, Rochester, MN, USA.
Ryan S D'SouzaDepartment of Anesthesiology and Perioperative Medicine, Division of Pain Medicine, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0002-4601-9837

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence was introduced 60 years ago and has evolved immensely since that time. While artificial intelligence is found in nearly all aspects of our life, the use of artificial intelligence in the healthcare industry has only recently become apparent and more widely discussed. It is expected that artificial intelligence will allow improved disease recognition, treatment optimization, cost and time savings, product development, decision making, and marketing. For pain medicine specifically, these same benefits will be translatable and we can expect better disease recognition and treatment selection. As adoption occurs with this impressive technology, it will be imperative for the pain medicine community to be informed on proper definitions and expected use cases for artificial intelligence. Our objective was to provide pain medicine physicians an overview of artificial intelligence, including important definitions to aid understanding, and to offer potential clinical applications pertinent to the specialty.

Indexed as

artificial intelligencechronic paineducationpain medicine

Identifiers

PMID38328019
PMCPMC10848920

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.