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IDCCD: evaluation of deep learning for early detection caries based on ICDAS Noer Fadilah, Rina Putri; Rikmasari, Rasmi; Akbar, Saiful; Setiawan, Arlette Suzy
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp381-392

Abstract

Dental caries is a common oral disease in children, influenced by environmental, psychological, behavioral, and biological factors. The American academy of pediatric dentistry recommends screening from the time the first tooth erupts or at one year of age to prevent caries, which mostly affects children from racial and ethnic minorities. In Indonesia, the 2023 health survey reported a caries prevalence of 84.8% in children aged 5-9 years. This research introduces early caries detection using three deep learning models: faster-RCNN, you only look once (YOLO) V8, and detection transformer (DETR), using Indonesian dental caries characteristic datasets (IDCCD) focused on Indonesian data with international caries detection and assessment system (ICDAS) classification D0 to D6. The results showed that YOLO V8-s and DETR gave good results, with mean average precision (mAP) of 41.8% and 41.3% for intersection over union (IoU) 50, and 24.3% and 26.2% for IoU 50:90. Precision-recall (PR) curves show that both models have high precision at low recall (0 to 0.2), but precision decreases sharply as recall increases. YOLO V8-s showed a slower and more regular decrease in precision, indicating a more stable performance compared to DETR.
Sosialisasi Aplikasi HI Bogi Artificial Intelligence Sebagai Sarana Peningkatan Pengetahuan Kesehatan Gigi dan Deteksi Karies Gigi pada Keluarga Militer di Kota Cimahi Noer Fadilah, Rina Putri; Sundawan, Kertamaya; Saephasa, Togap
Jurnal Abdimas Kartika Wijayakusuma Vol 7 No 1 (2026): Jurnal Abdimas Kartika Wijayakusuma
Publisher : LPPM Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26874/jakw.v7i1.1125

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan kesehatan gigi dan kemampuan deteksi dini karies gigi melalui penerapan aplikasi HI Bogi Artificial Intelligence (AI) pada keluarga militer di Kota Cimahi. Metode yang digunakan adalah Community-Based Research (CBR) dengan pendekatan Participatory Action Research (PAR), yang menekankan keterlibatan aktif masyarakat dalam setiap tahapan kegiatan, mulai dari perencanaan, pelaksanaan, hingga evaluasi. Kegiatan dilakukan melalui tahapan perizinan dan koordinasi dengan pihak wilayah militer, persiapan logistik, sosialisasi, serta pelatihan penggunaan aplikasi HI Bogi. Evaluasi dilakukan menggunakan instrumen pre-test dan post-test untuk mengukur tingkat pengetahuan peserta sebelum dan sesudah kegiatan. Hasil analisis menunjukkan adanya peningkatan rata-rata skor pengetahuan yang mengindikasikan terjadi peningkatan keseragaman pemahaman antar peserta. Temuan ini menunjukkan bahwa penerapan aplikasi HI Bogi AI efektif dalam meningkatkan pengetahuan dan kesadaran keluarga militer terhadap pentingnya menjaga kesehatan gigi dan mulut. Kegiatan ini juga memperkuat kolaborasi antara tim pengabdian dan komunitas dalam memanfaatkan teknologi digital untuk kesehatan masyarakat.
Effect of apatite cement on osteoblast cell numbers in alveolar sockets after tooth extraction in rabbits: an experimental study Supriatna, Andi; Noer Fadilah, Rina Putri; Dewi, Zwista Yulia; Yuniar, Nindya; Fitri, Dinda Kurnia
Padjadjaran Journal of Dentistry Vol 38, No 2 (2026): July 2026
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/pjd.vol38no2.70901

Abstract

Introduction: Tooth extraction damages soft and hard tissues, followed by alveolar bone resorption, which can interfere with the healing process and prosthetic rehabilitation. One effort to minimize alveolar bone resorption is the use of graft materials such as apatite cement, which is biocompatible and osteoconductive. This study aimed to analyze the effect of apatite cement on osteoblast cell numbers during alveolar socket healing following tooth extraction in rabbits. Methods: This study used a true experimental design with a post-test-only control group design. The study objects were biological materials placed in the alveolar sockets of New Zealand White rabbits, which were divided into a control group, a tooth extraction group without apatite cement administration, and a tooth extraction group with apatite cement administration. Histological observations were conducted on days 3, 7, and 14, representing the inflammatory, proliferative, and early remodeling phases of rabbit socket healing, respectively.  The data were analyzed statistically using normality and homogeneity tests, followed by the one-way ANOVA statistical test. Results: The mean osteoblast cell counts in the apatite cement group were significantly higher than those in the control group on days 3, 7, and 14. The highest osteoblast count was observed on day 14, with mean values of 28.93 ± 3.57 cells/field in the apatite cement group compared with 0.80 ± 0.35 cells/field in the control group (p < 0.05). One-way ANOVA demonstrated significant differences among the experimental groups. Conclusion: Apatite cement administration increased osteoblast cell numbers in the alveolar socket after tooth extraction in rabbits, suggesting its potential to promote early osteogenic activity during the initial stages of socket healing.