Evidence map›Paper›PMID 39820789›Full record

ReviewOral and maxillofacial surgery2025

The current landscape of artificial intelligence in oral and maxillofacial surgery- a narrative review.

Rushil Rajiv Dang, Balram Kadaikal, Sam El Abbadi, Branden R Brar, Amit Sethi, Radhika Chigurupati

Abstract readReview
PubMed Publisher
In one paragraph

Review in Oral and maxillofacial surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Rushil Rajiv Dang *Department of Oral and Maxillofacial, Boston University and Boston Medical Center, 635 Albany Street, 02118, Boston, MA, USA. rushilrd@bu.edu.
Balram Kadaikal *Henry M. Goldman School of Dental Medicine, Boston University, Boston, MA, USA.
Sam El AbbadiConsultant, Department of Plastic, Reconstructive and Aesthetic Surgery, University Hospital OWL, Campus Klinikum Bielefeld, Bielefeld, Germany.
Branden R BrarDepartment of Oral and Maxillofacial, Boston University and Boston Medical Center, Boston, MA, USA.
Amit SethiDepartment of Oral and Maxillofacial, Boston University and Boston Medical Center, Boston, MA, USA.
Radhika ChigurupatiDepartment of Oral and Maxillofacial surgery, Boston Medical Center, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis narrative review aims to explore the current applications and future prospects of AI within the subfields of oral and maxillofacial surgery (OMS), emphasizing its potential benefits and anticipated challenges.

methodsA detailed review of the literature was conducted to evaluate the role of AI in oral and maxillofacial surgery. All domains within OMS were reviewed with a focus on diagnostic, therapeutic and prognostic interventions.

resultsAI has been successfully integrated into surgical specialties to enhance clinical outcomes. In OMS, AI demonstrates potential to improve clinical and administrative workflows in both ambulatory and hospital-based settings. Notable applications include more accurate risk prediction, minimally invasive surgical techniques, and optimized postoperative management.

conclusionOMS stands to benefit enormously from the integration of AI. However, significant roadblocks, such as ethical concerns, data security, and integration challenges, must be addressed to ensure effective adoption. Further research and innovation are needed to fully realize the potential of AI in this specialty.

Indexed as

Artificial IntelligenceOral Surgical ProceduresSurgery, OralHumansArtificial intelligenceOral and maxillofacial surgery

Identifiers

PMID39820789

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.