ArticleJournal of pain research2025
Guidelines From the American Society of Pain and Neuroscience for Using Artificial Intelligence in Interventional Spine and Nerve Treatment.
Article in Journal of pain research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Artificial Intelligence in Neuropathic Pain: From Mechanisms to Neuromodulation and Regenerative Strategies.Current pain and headache reports · 2026Review
- Leveraging artificial intelligence to optimize neuromodulation in the treatment of patients with chronic pain.Frontiers in pain research (Lausanne, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
32 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Artificial intelligence (AI) is rapidly evolving and becoming more ubiquitous. Significant advancements have been made in the last few years, driving rapidly increasing adoption. The scale of publications on AI makes it difficult to keep abreast of relevant findings. Objective: The ASPN Artificial Intelligence Guidelines are designed to help clinicians understand AI and implement it into their practice. This Neuron Project is designed to evolve with the changing landscape of AI. Methods: An expert panel was chosen to discuss and write the best practice guidelines on AI. The primary authors conducted a literature search on PubMed, cross-referencing key terms in pain management and AI. After a thorough review of the current literature, the information collected was divided into broad categories of potential benefits, potential harms, and ways to ensure the benefits outweigh the potential harms of AI. These guidelines include only the most essential aspects of AI that clinicians need to know and understand before implementing AI into their practice. Results: Over 12,000 articles were found using the above search results. Many articles were reviews and clinical guidelines. The framework created from these guidelines allowed authors to fill in knowledge gaps and discuss the most critical elements pain clinicians should comprehend about AI. Conclusion: All authors achieved consensus on guidelines for implementing and using AI in pain management following a process of critical review and edits by the entire group of authors. All authors approved final guidelines. Discussion: The field of artificial intelligence is rapidly growing. As it expands into healthcare, it is necessary to prevent breaches of sensitive data and potential harm to patients. Guidelines that constantly evolve and grow with expanding indications for AI are essential to maximize benefit and prevent harm. This paper is part of ASPN's Neuron Project and is designed to update continuously as this field evolves.
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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.