Evidence map›Paper›PMID 36917511›Full record

ArticleThe Angle orthodontist2023

The accuracy of artificial intelligence-based virtual assistants in responding to routinely asked questions about orthodontics.

Anthony Perez-Pino, Sumit Yadav, Madhur Upadhyay, Lauren Cardarelli, Aditya Tadinada

Open access · diamondAbstract read
In one paragraph

Article in The Angle orthodontist, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
7.4field-weighted citation impact, top 3% of its field
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

7 citing papers in PubMed, 15 citations in OpenAlex.

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  6. Comparative Analysis of Artificial Intelligence Virtual Assistant and Large Language Models in Post-Operative Care.European journal of investigation in health, psychology and education · 2024
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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

5 authors.

Anthony Perez-Pino
Sumit Yadav
Madhur Upadhyay
Lauren Cardarelli
Aditya Tadinada

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the utility and efficiency of four voice-activated, artificial intelligence-based virtual assistants (Alexa, Google Assistant, Siri, and Cortana) in addressing commonly asked patient questions in orthodontic offices. MATERIALS AND

methodsTwo orthodontists, an orthodontic resident, an oral and maxillofacial radiologist, and a dental student used a standardized list of 12 questions to query and evaluate the four most common commercial virtual assistant devices. A modified Likert scale was used to evaluate their performance.

resultsGoogle Assistant had the lowest (best) mean score, followed by Siri, Alexa, and Cortana. The score of Google Assistant was significantly lower than Alexa and Cortana. There was significant variablity in virtual assistant response scores among the evaluators, with the exception of Amazon Alexa. Lower scores indicated superior efficiency and utility.

conclusionsThe common commercially available virtual assistants tested in this study showed significant differences in how they responded to users. There were also significant differences in their performance when responding to common orthodontic queries. An intelligent virtual assistant with evidence-based responses specifically curated for orthodontics may be a good solution to address this issue. The investigators in this study agreed that such a device would provide value to patients and clinicians.

Indexed as

OrthodonticsVoiceArtificial IntelligenceHumansOrthodontistsArtificial intelligenceVirtual assistants

Identifiers

PMID36917511
PMCPMC10294585
OpenAlexW4324129456

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.