Evidence map›Paper›PMID 40585609›Full record

ReviewCureus2025

Artificial Intelligence Tools in Dentistry: A Systematic Review on Their Application and Outcomes.

Manjulika Tyagi, Shailesh Jain, Maitreyi Ranjan, Sahba Hassan, Nikhil Prakash, Dinesh Kumar, Ayush Kumar, Spriha Singh

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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.

Manjulika TyagiProsthodontics, Subharti Dental College and Hospital, Swami Vivekanand Subharti University, Meerut, IND.
Shailesh JainProsthodontics, Bhojia Dental College and Hospital, Baddi, IND.
Maitreyi RanjanMicrobiology, School of Dental Sciences, Sharda University, Greater Noida, IND.
Sahba HassanProsthodontics and Crown and Bridge, DJ College of Dental Sciences and Research, Modinagar, IND.
Nikhil PrakashProsthodontics, DJ College Of Dental Sciences and Research, Muradnagar, IND.
Dinesh KumarOral Surgery, M.M. College of Dental Sciences and Research, Mullana, IND.
Ayush KumarDentistry, Dr. Harvansh Singh Judge Institute of Dental Sciences & Hospital, Panjab University, Chandigarh, IND.
Spriha SinghProsthodontics, KVG Dental College and Hospital, Sullia, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) in dentistry is rapidly getting recognized, altering the way that dentists treat patients and carry out clinical tasks. This systematic review investigates the integration of AI technologies into dental practice, with a particular focus on their impact on diagnostic accuracy, treatment planning, and operational efficiency. AI algorithms, especially those utilizing deep learning, have demonstrated exceptional proficiency in analyzing dental images, facilitating early and accurate detection of conditions such as caries, periodontal disease, and oral malignancies. Relevant literature was identified through an extensive search of electronic databases, including PubMed, Medline, Google Scholar, Scopus, and Web of Science, covering publications from 2019 to 2024. A total of 39 full-text articles were selected based on predefined inclusion and exclusion criteria, and their quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. From an initial pool of 342 articles, the 39 included studies revealed that AI-driven tools streamline administrative tasks, automate routine processes, and enhance overall practice efficiency, thereby reducing operational time. AI has exhibited significant potential in a wide range of dental fields, including radiology, periodontics, prosthodontics, orthodontics, oncology, diagnostic dentistry, and patient management. The findings highlight the promising role of AI in improving clinical outcomes and patient care while emphasizing the importance of balancing technological advancements with ethical considerations and human expertise. This review underscores the transformative potential of AI in modern dental practice and stresses the need for continued research and development in this dynamic and rapidly evolving field.

Indexed as

artificial intelligence in dentistryartificial neural networksconvolutional neural networksdeep learningmachine learning

Identifiers

PMID40585609
PMCPMC12206247

What OpenQuestion holds

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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.