Evidence map›Paper›PMID 37074486›Full record

ArticleAnnals of biomedical engineering2023

Potential Use of Artificial Intelligence in Infectious Disease: Take ChatGPT as an Example.

Kunming Cheng, Zhiyong Li, Yongbin He, Qiang Guo, Yanqiu Lu, Shuqin Gu, Haiyang Wu

Abstract readLetter
In one paragraph

Article in Annals of biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–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

36 citing papers in PubMed.

  1. Article
  2. Observational
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  18. Large language models and generative AI in telehealth: a responsible use lens.Journal of the American Medical Informatics Association : JAMIA · 2024
    Review
  19. Article
  20. Article
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

7 authors.

Kunming Cheng *Department of Intensive Care Unit, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Zhiyong Li *Department of Orthopedics, Baodi Clinical College of Tianjin Medical University, Tianjin, China.
Yongbin He *School of Sport Medicine and Rehabilitation, Beijing Sport University, Beijing, China.
Qiang GuoDepartment of Orthopedics, Baodi Clinical College of Tianjin Medical University, Tianjin, China.
Yanqiu LuDepartment of Intensive Care Unit, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. yanqiul@163.com.
Shuqin GuDuke Human Vaccine Institute, Duke University Medical Center, Durham, NC, USA. shuqin.gu@duke.edu.
Haiyang WuDepartment of Graduate School, Tianjin Medical University, Tianjin, China. wuhaiyang2021@tmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past month, a new AI model called Chatbot Generative Pre-trained Transformer (ChatGPT), has received enormous attention in the media and scientific communities due to its ability to process and respond to commands in a humanistic fashion. As reported, five days after its launch, the number of registered users of ChatGPT exceeded one million, and its monthly active users had exceeded 100 million two months later, making it the most rapidly growing consumer application in history. The advent of ChatGPT has further brought about new ideas and challenges in the realm of infectious disease. In view of this, in order to evaluate the potential use of ChatGPT in clinical practice and scientific research of infectious disease, we conducted a brief online survey by using the publicly available ChatGPT webpage. Also, the present study also talks about the relevant social and ethical issues related to this program.

Indexed as

Artificial IntelligenceCommunicable DiseasesElectric Power SuppliesHumansSoftwareArtificial intelligenceChatbotsChatGPTInfectious disease

Identifiers

PMID37074486
PMCPMC10116900

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.