Evidence map›Paper›PMID 39170734›Full record

ArticleData in brief2024

Varying views of maxillary and mandibular aspects of teeth: A dataset.

Shweta Chaudhary, Preetam Shah, Priyanka Paygude, Shwetambari Chiwhane, Pratibha Mahajan, Prashant Chavan, Manisha Kasar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Shweta ChaudharyBharati Vidyapeeth Deemed to be University Dental College and Hospital, Katraj, Pune, India.
Preetam ShahBharati Vidyapeeth Deemed to be University Dental College and Hospital, Katraj, Pune, India.
Priyanka PaygudeBharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.
Shwetambari ChiwhaneSymbiosis Institute of Technology, Symbiosis International University, Pune, India.
Pratibha MahajanDepartment of Artificial Intelligence, Vishwakarma University, Pune, India.
Prashant ChavanBharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.
Manisha KasarBharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real teeth or dental image datasets are a valuable resource that is transforming the field of dentistry by enabling automation, improving diagnostics and accelerating research and development.This article presents a comprehensive dataset containing 9,562 images of healthy teeth (noncarious) from children aged 1 to 14 years. The images capture different views of the teeth, including maxillary (upper) and mandibular (lower) arches, front, right, left, and occlusal (biting surface) views. These images are stored under eight subcategories in the Mendeley repository, a platform for research data. The potential application of this dataset involves using machine learning to analyze the dental condition. This could provide a faster analysis and facilitate remote assessment of dental conditions in underserved areas. Overall, this dataset seems like a promising tool for advancing dental care through the power of machine learning.

Indexed as

Dental photographyMandibular viewMaxillary viewMixed dentitionNon-carious teethOcclusal viewPermanent dentitionPrimary dentition

Identifiers

PMID39170734
PMCPMC11334821

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.