Work

Deep learning-based prediction of possibility for immediate implant placement using panoramic radiography

Year: 2025

Type: article

Abstract: In this study, we investigated whether deep learning-based prediction of immediate implant placement is possible. Panoramic radiographs of 201 patients with 874 teeth (Group 1: 440 teeth difficult to place implant immediately after extraction, Group 2: 434 teeth possible of immediate implant placement after extraction) for extraction were evaluated for the training and testing of a deep learning model. DenseNet121, ResNet18, ResNet101, ResNeXt101, InceptionNetV3, and InceptionResNetV2 were used. Each model was trained using preprocessed dental data, and the dataset was divided into training, validation, and test sets to evaluate model performance. For each model, the sensitivity, precision, accuracy, balanced accuracy, and F1-score were all greater than 0.90. The results of this study confirm that deep-learning-based prediction of the possibility of immediate implant placement is possible at a fairly accurate level.

Source: Scientific Reports

DOI: 10.1038/s41598-025-89219-2

Authors: Sae Byeol Mun, Hun Jun Lim, Young Jae Kim, Bong Chul Kim, Kwang Gi Kim

Institutions: Gachon University, Wonkwang University Daejeon Dental Hospital, Wonkwang University, Gachon University Gil Medical Center

Language: English

Topic: Dental Radiography and Imaging

Subfield: Oral Surgery

Field: Dentistry

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,690