Evidence map›Paper›PMID 37507396›Full record

ReviewInternational journal of oral science2023

ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model.

Hanyao Huang, Ou Zheng, Dongdong Wang, Jiayi Yin, Zijin Wang, Shengxuan Ding, Heng Yin, Chuan Xu, Renjie Yang, Qian Zheng and 1 more

Abstract readReview
In one paragraph

Review in International journal of oral science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 3 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

102 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Transformer-based models in dentistry: a systematic review.BMC medical informatics and decision making · 2026
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42 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

11 authors.

Hanyao Huang *State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China. huanghanyao_cn@scu.edu.cn.ORCID 0000-0002-6805-0157
Ou Zheng *Department of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, USA. ouzheng1993@knights.ucf.edu.ORCID 0000-0001-6313-8566
Dongdong WangDepartment of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, USA.
Jiayi YinState Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Zijin WangDepartment of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, USA.
Shengxuan DingCollege of Transportation Engineering, University of Central Florida, Orlando, USA.
Heng YinState Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Chuan XuSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China.
Renjie YangState Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Eastern Clinic, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Qian ZhengState Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Bing ShiState Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact various fields. This paper mainly discusses the future applications of LLMs in dentistry. We introduce two primary LLM deployment methods in dentistry, including automated dental diagnosis and cross-modal dental diagnosis, and examine their potential applications. Especially, equipped with a cross-modal encoder, a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations. We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application. While LLMs offer significant potential benefits, the challenges, such as data privacy, data quality, and model bias, need further study. Overall, LLMs have the potential to revolutionize dental diagnosis and treatment, which indicates a promising avenue for clinical application and research in dentistry.

Indexed as

Artificial IntelligenceDentistry

Identifiers

PMID37507396
PMCPMC10382494

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.