Evidence map›Paper›PMID 42556100›Full record

ReviewInternational dental journal2026

Artificial Intelligence Meets Oral Medicine: Extending the Capabilities of Human Intelligence.

Xinjian Ye, Tingfeng Zha, Xun Xie, Yi Xu, Li Mei, Rui Zhang, Zhiyong Wang, Qianming Chen

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International dental journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Xinjian YeStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China; Department of Developmental Biology, Harvard School of Dental Medicine, Boston, Massachusetts, USA.
Tingfeng ZhaStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China.
Xun XieStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China.
Yi XuStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China.
Li MeiDepartment of Oral Sciences, Faculty of Dentistry, University of Otago, Dunedin, New Zealand.
Rui ZhangStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China. Electronic address: zhangrui46@zju.edu.cn.
Zhiyong WangStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China. Electronic address: wzy0809@zju.edu.cn.
Qianming ChenStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesOral medicine is an interdisciplinary field that focuses on non-odontogenic diseases. The emergence of artificial intelligence (AI) offers new opportunities to strengthen human perceptual, cognitive, and operational capacities. This review aims to provide clinicians and researchers with an explanatory, practical, and accessible overview of AI in oral medicine.

methodsThis review synthesizes recent findings identified through structured online searches. Subtopics related to AI technologies in oral medicine were categorized into four areas: image recognition, decision-making support, therapy collaboration, and existing challenges. Particular emphasis was placed on oral mucosal diseases, oral cancer, and orofacial pain.

resultsAI enhances clinical workflows by achieving high-accuracy lesion detection, segmentation, and classification from diverse image types. It enables data-driven diagnosis, risk stratification, and prognosis prediction. Furthermore, AI facilitates precise surgical planning, real-time guidance, and personalized postoperative management.

conclusionsAI is poised to transform Oral Medicine into an intelligence-augmented discipline. However, its full clinical integration requires overcoming challenges related to data quality, algorithmic robustness, ethical governance, and the need for robust clinical validation.

Indexed as

Artificial IntelligenceOral MedicineHumansMouth DiseasesMouth NeoplasmsArtificial intelligenceDeep learningOral diseaseOral medicine

Identifiers

PMID42556100
PMCPMC13470172

What Socratic 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 Socratic graph.