Real-Time Caries Detection of Bitewing Radiographs Using a Mobile Phone and an Artificial Neural Network: A Pilot Study
نویسندگان
چکیده
This pilot study aimed to implement and assess the performance of an experimental artificial intelligence (AI) mobile phone app in real-time detection caries lesions on bitewing radiographs (BWRs) with use a back-facing video camera. The author trained EfficientDet-Lite1 neural network using 190 radiographic images from Internet. model was deployed Google Pixel 6 used detect ten additional Internet BWRs. sensitivity/precision/F1 scores ranged 0.675/0.692/0.684 0.575/0.719/0.639 for aggregate handheld static BWRs versus stationary scanning moving BWRs, respectively. Averaging results, AI detected—in real time—62.5% precision 70.6% When combined app’s relative ease speed potential global accessibility, this proof-of-concept could quite literally place AI’s vast improving patient care dentists’ hands.
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ژورنال
عنوان ژورنال: Oral
سال: 2023
ISSN: ['2673-6373']
DOI: https://doi.org/10.3390/oral3030035