Deep Learning–Based Detection of Root Numbers in Maxillary Premolars

Deep learning models showed reliable performance in predicting root numbers of maxillary premolars from panoramic radiographs, with the ensemble model achieving the most stable and accurate results. These findings indicate that deep learning systems may serve as a supportive tool in clinical decision-making.

Authors

Institutions

Publication Details

Journal
International Endodontic Journal
Published
2026-01-06
DOI
https://doi.org/10.1111/iej.70091
Primary Topic
Dental Radiography and Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deep Learning–Based Detection of Root Numbers in Maxillary Premolars

Cem Azgari, Ecem Azgari, Hesna Sazak Öveçoğlu
International Endodontic Journal
Dental Radiography and Imaging
article

Deep Learning–Based Detection of Root Numbers in Maxillary Premolars

Cem Azgari, Ecem Azgari, Hesna Sazak Öveçoğlu
article en

Abstract

Deep learning models showed reliable performance in predicting root numbers of maxillary premolars from panoramic radiographs, with the ensemble model achieving the most stable and accurate results. These findings indicate that deep learning systems may serve as a supportive tool in clinical decision-making.

International Endodontic Journal
Sabancı Üniversitesi (TR), Marmara University (TR)
Openalex Percentile: Top 97%
Dental Radiography and Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.