start-ver=1.4
cd-journal=joma
no-vol=11
cd-vols=
no-issue=6
article-no=
start-page=815
end-page=
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2021
dt-pub=20210530
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=Multi-Task Deep Learning Model for Classification of Dental Implant Brand and Treatment Stage Using Dental Panoramic Radiograph Images
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=It is necessary to accurately identify dental implant brands and the stage of treatment to ensure efficient care. Thus, the purpose of this study was to use multi-task deep learning to investigate a classifier that categorizes implant brands and treatment stages from dental panoramic radiographic images. For objective labeling, 9767 dental implant images of 12 implant brands and treatment stages were obtained from the digital panoramic radiographs of patients who underwent procedures at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2020. Five deep convolutional neural network (CNN) models (ResNet18, 34, 50, 101 and 152) were evaluated. The accuracy, precision, recall, specificity, F1 score, and area under the curve score were calculated for each CNN. We also compared the multi-task and single-task accuracies of brand classification and implant treatment stage classification. Our analysis revealed that the larger the number of parameters and the deeper the network, the better the performance for both classifications. Multi-tasking significantly improved brand classification on all performance indicators, except recall, and significantly improved all metrics in treatment phase classification. Using CNNs conferred high validity in the classification of dental implant brands and treatment stages. Furthermore, multi-task learning facilitated analysis accuracy.
en-copyright=
kn-copyright=

en-aut-name=SukegawaShintaro
en-aut-sei=Sukegawa
en-aut-mei=Shintaro
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=YoshiiKazumasa
en-aut-sei=Yoshii
en-aut-mei=Kazumasa
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=HaraTakeshi
en-aut-sei=Hara
en-aut-mei=Takeshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

en-aut-name=MatsuyamaTamamo
en-aut-sei=Matsuyama
en-aut-mei=Tamamo
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=

en-aut-name=YamashitaKatsusuke
en-aut-sei=Yamashita
en-aut-mei=Katsusuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=5
ORCID=

en-aut-name=NakanoKeisuke
en-aut-sei=Nakano
en-aut-mei=Keisuke
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=6
ORCID=

en-aut-name=TakabatakeKiyofumi
en-aut-sei=Takabatake
en-aut-mei=Kiyofumi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=7
ORCID=

en-aut-name=KawaiHotaka
en-aut-sei=Kawai
en-aut-mei=Hotaka
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=8
ORCID=

en-aut-name=NagatsukaHitoshi
en-aut-sei=Nagatsuka
en-aut-mei=Hitoshi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=9
ORCID=

en-aut-name=FurukiYoshihiko
en-aut-sei=Furuki
en-aut-mei=Yoshihiko
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=10
ORCID=

affil-num=1
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=

affil-num=2
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=

affil-num=3
en-affil=Department of Intelligence Science and Engineering, Graduate School of Natural Science and Technology, Gifu University
kn-affil=

affil-num=4
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=

affil-num=5
en-affil=Polytechnic Center Kagawa
kn-affil=

affil-num=6
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=

affil-num=7
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=

affil-num=8
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=

affil-num=9
en-affil=Dentistry and Pharmaceutical Sciences, Department of Oral Pathology and Medicine, Okayama University Graduate School of Medicine
kn-affil=

affil-num=10
en-affil=Department of Oral and Maxillofacial Surgery, Kagawa Prefectural Central Hospital
kn-affil=
en-keyword=multi-task learning
kn-keyword=multi-task learning
en-keyword=deep learning
kn-keyword=deep learning
en-keyword=artificial intelligence
kn-keyword=artificial intelligence
en-keyword=dental implant
kn-keyword=dental implant
en-keyword=classification
kn-keyword=classification
END