Evidence map›Paper›PMID 38809404›Full record

ReviewCurrent pain and headache reports2024

The Ethical Stewardship of Artificial Intelligence in Chronic Pain and Headache: A Narrative Review.

Maria Emilia Mazzolenis, Evgeny Bulat, Michael E Schatman, Chris Gumb, Christopher J Gilligan, Robert J Yong

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pain and headache reports, 2024. 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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. 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

6 authors.

Maria Emilia Mazzolenis *John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
Evgeny Bulat *Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, 02115, MA, USA.
Michael E SchatmanDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, Department of Population Health - Division of Medical Ethics, New York University Grossman School of Medicine, New York, NY, USA.
Chris GumbJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
Christopher J GilliganDepartment of Anesthesiology, Robert Wood Johnson University Hospital, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Robert J YongDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, 02115, MA, USA. ryong@bwh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewAs artificial intelligence (AI) and machine learning (ML) are becoming more pervasive in medicine, understanding their ethical considerations for chronic pain and headache management is crucial for optimizing their safety. RECENT

findingsWe reviewed thirty-eight editorial and original research articles published between 2018 and 2023, focusing on the application of AI and ML to chronic pain or headache. The core medical principles of beneficence, non-maleficence, autonomy, and justice constituted the evaluation framework. The AI applications addressed topics such as pain intensity prediction, diagnostic aides, risk assessment for medication misuse, empowering patients to self-manage their conditions, and optimizing access to care. Virtually all AI applications aligned both positively and negatively with specific medical ethics principles. This review highlights the potential of AI to enhance patient outcomes and physicians' experiences in managing chronic pain and headache. We emphasize the importance of carefully considering the advantages, disadvantages, and unintended consequences of utilizing AI tools in chronic pain and headache, and propose the four core principles of medical ethics as an evaluation framework.

Indexed as

Artificial IntelligenceChronic PainHeadacheEthics, MedicalHumansPain ManagementArtificial intelligenceChronic headacheChronic painMachine learningMedical ethics

Identifiers

PMID38809404

What OpenQuestion holds

Textmetadata
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.