Evidence map›Paper›PMID 36924908›Full record

ArticleAmerican journal of obstetrics and gynecology2023

Chat Generative Pre-trained Transformer: why we should embrace this technology.

Martin R Chavez, Thomas S Butler, Patricia Rekawek, Hye Heo, Wendy L Kinzler

Abstract read
PubMed Publisher
In one paragraph

Article in American journal of obstetrics and gynecology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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

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  10. Exploring the landscape of AI-assisted decision-making in head and neck cancer treatment: a comparative analysis of NCCN guidelines and ChatGPT responses.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

5 authors.

Martin R ChavezDivision of Maternal-Fetal Medicine, Department of Obstetrics Gynecology, New York University Langone Hospital-Long Island, New York University Long Island School of Medicine, Mineola, NY. Electronic address: Martin.Chavez@nyulangone.org.
Thomas S ButlerNew York University Langone Reproductive Specialists of New York, New York University Langone Hospital-Long Island, New York University Langone Long Island School of Medicine, Mineola, New York.
Patricia RekawekDivision of Maternal-Fetal Medicine, Department of Obstetrics Gynecology, New York University Langone Hospital-Long Island, New York University Long Island School of Medicine, Mineola, NY.
Hye HeoDivision of Maternal-Fetal Medicine, Department of Obstetrics Gynecology, New York University Langone Hospital-Long Island, New York University Long Island School of Medicine, Mineola, NY.
Wendy L KinzlerDivision of Maternal-Fetal Medicine, Department of Obstetrics Gynecology, New York University Langone Hospital-Long Island, New York University Long Island School of Medicine, Mineola, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the advent of artificial intelligence that not only can learn from us but also can communicate with us in plain language, humans are embarking on a brave new future. The interaction between humans and artificial intelligence has never been so widespread. Chat Generative Pre-trained Transformer is an artificial intelligence resource that has potential uses in the practice of medicine. As clinicians, we have the opportunity to help guide and develop new ways to use this powerful tool. Optimal use of any tool requires a certain level of comfort. This is best achieved by appreciating its power and limitations. Being part of the process is crucial in maximizing its use in our field. This clinical opinion demonstrates the potential uses of Chat Generative Pre-trained Transformer for obstetrician-gynecologists and encourages readers to serve as the driving force behind this resource.

Indexed as

Artificial IntelligenceMedicineHealth PersonnelHumansLanguageTechnologyartificial intelligenceChat Generative Pre-trained Transformerfuture of medicinelarge language modelsOpenAIplain conversational language interfaces

Identifiers

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.