Evidence map›Paper›PMID 41428389›Full record

ArticleJMIR research protocols2025

Efficacy of Artificial Intelligence-Assisted Appliances in the Selection of Tooth Shade: Protocol for an Observational Study.

Namita Zilpilwar, Sharayu Nimonkar, Surekha Godbole, Vikram Belkhode

Abstract readClinical Trial Protocol
In one paragraph

Article in JMIR research protocols, 2025. 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

4 authors.

Namita Zilpilwar *Department of Prosthodontics Crown and Bridge, Sharad Pawar Dental College and Hospital, Datta Meghe Institute Health Education and Research, Wardha, Maharashtra, India.ORCID 0009-0000-7046-8942
Sharayu NimonkarDepartment of Prosthodontics Crown and Bridge, Sharad Pawar Dental College and Hospital, Datta Meghe Institute Health Education and Research, Wardha, Maharashtra, India.ORCID 0000-0002-1188-7300
Surekha GodboleDepartment of Prosthodontics Crown and Bridge, Sharad Pawar Dental College and Hospital, Datta Meghe Institute Health Education and Research, Wardha, Maharashtra, India.ORCID 0000-0002-3642-9787
Vikram BelkhodeDepartment of Prosthodontics Crown and Bridge, Sharad Pawar Dental College and Hospital, Datta Meghe Institute Health Education and Research, Wardha, Maharashtra, India.ORCID 0000-0002-8667-5011

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate shade matching in dentistry is crucial for achieving aesthetic outcomes, with increasing patient expectations driving advancements in shade selection technologies. Color perception is influenced by multiple factors such as incident light, reflection, absorption, observer variability, and environmental conditions. The evolution of shade-matching tools now includes digital and artificial intelligence (Al)-assisted appliances aimed at improving accuracy and ease of use.

objectiveThis study aims to compare and evaluate the efficacy of AI-assisted appliances, namely, smartphone cameras, digital single-lens reflex (DSLR) cameras, and intraoral scanners in selecting tooth shades in clinical practice.

methodsThis observational study conducted at the Department of Prosthodontics and Crown & Bridge aims to evaluate shade selection methods in 221 participants recruited from the outpatient department based on specific inclusion and exclusion criteria, including age, oral health status, and informed consent. Three devices will be used for shade selection: a smartphone camera (iPhone 12, iOS 12.5.2) for quick, noninvasive, and accessible image capture; a DSLR camera (Canon EOS 200D) to obtain high-resolution images under standardized lighting for enhanced color accuracy; and an intraoral scanner (CEREC Primescan, Dentsply Sirona) offering precise 3D mapping and digital shade analysis. This multidevice approach allows for a comparative evaluation of conventional and advanced digital tools in clinical shade matching. The primary objective is to assess the effectiveness of commonly available digital teeth in accurately selecting tooth shades. Our study anticipates the following outcomes: validation of smartphone cameras as simple, economical, and efficient tools for basic shade matching; demonstration of DSLR cameras' superiority in resolution and lighting control for improved accuracy; and confirmation of intraoral scanners as precise, customizable devices that offer a high level of digital integration. Statistical analyses will include sensitivity, specificity, and subgroup evaluations to compare the performance of each device. The findings are expected to show that both DSLR and smartphone cameras can match the effectiveness of intraoral scanners, offering viable alternatives for clinical use.

resultsThis study was intramurally funded in December 2024. Data collection is scheduled to commence following the publication of this study protocol. As of submission, no participants have been recruited, and data analysis is yet to begin. Results are expected to be completed and published in early January 2026.

conclusionsThis study aims to establish a standard protocol for the use of Al-assisted, easily accessible tools such as smartphones and DSLRs for dental shade selection. These devices, being user-friendly and nontechnical, could democratize the process of shade matching, benefiting both clinicians and patients by improving restoration outcomes while reducing costs and complexity. Our results will contribute to the growing body of digital dentistry literature and support the integration of practical Al tools in everyday clinical practice.

trial registrationClinical Trials Registry-India CTRI/2024/07/070002; https://tinyurl.com/4pt5eutb. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/68160.

Indexed as

Artificial IntelligenceProsthesis ColoringToothColorHumansObservational Studies as TopicSmartphoneCEILAB coordinatesDSLR cameraintraoral scannersmartphonevita classic

Identifiers

PMID41428389
PMCPMC12770922

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Registered trials

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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.