Publication Name	World Journal of Clinical Cases
Manuscript ID	92818
Country	Armenia

Received	2024-02-06 15:18
Peer-Review Started	2024-02-06 15:18
To Make the First Decision
Return for Revision	2024-08-23 18:02
Revised	2024-08-25 20:36
Second Decision	2024-09-12 02:40
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-09-12 08:09
Articles in Press	2024-09-12 08:09
Publication Fee Transferred
Edit the Manuscript by Language Editor	2024-09-13 09:52
Typeset the Manuscript	2024-09-18 04:11
Publish the Manuscript Online	2024-09-24 02:54

ISSN	2307-8960 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
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Category	Dentistry, Oral Surgery & Medicine
Manuscript Type	Letter to the Editor
Article Title	Dental images classification and detection using meta-learning
Manuscript Source	Invited Manuscript
All Author List	Pradeep Kumar Yadalam, Raghavendra Vamsi Anegundi, Mario Alberto Alarcón-Sánchez and Artak Heboyan
ORCID	Author(s) ORCID Number Artak Heboyan http://orcid.org/0000-0001-8329-3205
Funding Agency and Grant Number
Corresponding Author	Artak Heboyan, DDS, MD, MSc, PhD, Associate Professor, Department of Prosthodontics, Yerevan State Medical University after Mkhitar Heratsi, Koryun 2, Yerevan 0025, Armenia. heboyan.artak@gmail.com
Key Words	Artificial intelligence; Meta-learning; Dental diagnosis; Image segmentation; Medical image interpretation; Dental radiography
Core Tip	Meta-learning offers a promising approach for achieving high-accuracy detection and diagnosis in dental radiographic image classification. This method holds significant promise for accurate and reliable prediction with less bias by leveraging its capability to learn from limited training data and generalize effectively to unseen dental X-ray categories.
Publish Date	2024-09-24 02:54
Citation	<p>Yadalam PK, Anegundi RV, Alarcón-Sánchez MA, Heboyan A. Dental images classification and detection using meta-learning. <i>World J Clin Cases</i> 2024; 12(32): 6559-6562</p>
URL	https://www.wjgnet.com/2307-8960/full/v12/i32/6559.htm
DOI	https://dx.doi.org/10.12998/wjcc.v12.i32.6559

Full Article (PDF)	WJCC-12-6559-with-cover.pdf
Manuscript File	92818_Auto_Edited_033112.docx
Answering Reviewers	92818-answering-reviewers.pdf
Audio Core Tip	92818-audio.mp4
Conflict-of-Interest Disclosure Form	92818-conflict-of-interest-statement.pdf
Copyright License Agreement	92818-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate	92818-non-native-speakers.pdf
Peer-review Report	92818-peer-reviews.pdf
Scientific Misconduct Check	92818-scientific-misconduct-check.png
Scientific Editor Work List	92818-scientific-editor-work-list.pdf
CrossCheck Report	92818-crosscheck-report.pdf
CrossCheck Report	92818-crosscheck-report.png