Evidence map›Paper›PMID 38028668›Full record

ReviewFrontiers in artificial intelligence2023

Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.

Chiranjib Chakraborty, Soumen Pal, Manojit Bhattacharya, Snehasish Dash, Sang-Soo Lee

Abstract readReview
In one paragraph

Review in Frontiers in artificial intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

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

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1 more citing papers are in PubMed but not listed here.

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

5 authors.

Chiranjib Chakraborty *Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal, India.
Soumen Pal *School of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Manojit Bhattacharya *Department of Zoology, Fakir Mohan University, Balasore, Odisha, India.
Snehasish DashSchool of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Sang-Soo LeeInstitute for Skeletal Aging and Orthopedic Surgery, Hallym University Chuncheon Sacred Heart Hospital, Chuncheon-si, Gangwon-do, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The release of ChatGPT has initiated new thinking about AI-based Chatbot and its application and has drawn huge public attention worldwide. Researchers and doctors have started thinking about the promise and application of AI-related large language models in medicine during the past few months. Here, the comprehensive review highlighted the overview of Chatbot and ChatGPT and their current role in medicine. Firstly, the general idea of Chatbots, their evolution, architecture, and medical use are discussed. Secondly, ChatGPT is discussed with special emphasis of its application in medicine, architecture and training methods, medical diagnosis and treatment, research ethical issues, and a comparison of ChatGPT with other NLP models are illustrated. The article also discussed the limitations and prospects of ChatGPT. In the future, these large language models and ChatGPT will have immense promise in healthcare. However, more research is needed in this direction.

Indexed as

AIChatbotChatGPTlarge language modelsmedical use

Identifiers

PMID38028668
PMCPMC10644239

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.