Evidence map›Paper›PMID 37307079›Full record

ReviewRheumatology (Oxford, England)2023

AI am a rheumatologist: a practical primer to large language models for rheumatologists.

Vincenzo Venerito, Emre Bilgin, Florenzo Iannone, Sedat Kiraz

Open access · hybridAbstract readReview
In one paragraph

Review in Rheumatology (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

27 citing papers in PubMed, 46 citations in OpenAlex.

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  15. Large language models and rheumatology: are we there yet?Rheumatology advances in practice · 2025
    Review
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  19. To trust or not to trust: evaluating the reliability and safety of AI responses to laryngeal cancer queries.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Vincenzo VeneritoRheumatology Unit, Department of Precision and Regenerative Medicine-Ionian Area, University of Bari 'Aldo Moro', Bari, Italy.ORCID 0000-0002-2573-5930
Emre BilginDivision of Rheumatology, Department of Internal Medicine, Hacettepe University Faculty of Medicine, Ankara, Turkey.ORCID 0000-0002-2260-4660
Florenzo IannoneRheumatology Unit, Department of Precision and Regenerative Medicine-Ionian Area, University of Bari 'Aldo Moro', Bari, Italy.ORCID 0000-0003-0474-5344
Sedat KirazDivision of Rheumatology, Department of Internal Medicine, Hacettepe University Faculty of Medicine, Ankara, Turkey.ORCID 0000-0003-2802-6061
Hacettepe University · TRUniversity of Bari Aldo Moro · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural language processing (NLP), a subclass of artificial intelligence, large language models (LLMs), and its latest applications, such as Generative Pre-trained Transformers (GPT), ChatGPT, or LLAMA, have recently become one of the most discussed topics. Up to now, artificial intelligence and NLP ultimately impacted several areas, such as finance, economics and diagnostic/scoring systems in healthcare. Another area that artificial intelligence has affected and will continue to affect increasingly is academic life. This narrative review will define NLP, LLMs and their applications, discuss the opportunities and challenges that components of academic society will experience in rheumatology, and discuss the impact of NLP and LLMs in rheumatology healthcare.

Indexed as

RheumatologistsRheumatologyArtificial IntelligenceHumansNatural Language Processingacademiachallengesgenerative pre-trained transformers (GPT)large language models (LLMs)Natural language processing (NLP)opportunitiesrheumatology

Identifiers

PMID37307079
PMCPMC10547503
OpenAlexW4380290798

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.