Automated Classification of Maxillary Sinus Ostium Patency Using a ConvNeXt-Tiny + DeiT Gated MLP-Based Hybrid Deep Learning Model: A Retrospective CBCT Study
Criterion: Q1 Article
Summary Info
Authors
TALO FURKAN,DÜGER NURULLAH,ARSLAN EMRE,YILDIRIM MUHAMMED,KAYA MAHMUT,ÖZER AHMET BEDRİ,TALO YILDIRIM TUBA
Journal
Diagnostics
Language
İngilizce
Scope
Uluslararası
Peer Review
Hakemli
DOI
10.3390/diagnostics16101512
Scoring Breakdown
Base Score:34.00
Base Score Breakdown
Diğer Makaleler2.00
Q1 Makalesi30.00
Özgün Makale2.00
Total (Base)34.00
Final Score:41.14
Applied Multipliers
1. in author order
(x1.00)
Hakemli
(x1.10)
Uluslararası
(x1.10)
Calculation
34.00
× 1.00
× 1.10
× 1.10
= 41.14
Calculated: 27.08.2026 02:02
Activity
Evaluation of Maxillary Sinus Membrane Morphology Using a Novel Hybrid CNN-ViT-Based Deep Learning Model: An Automated Classification Study