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All Journal Jurnal Kedokteran Gigi Terpadu
Rani Rahayu, Elma
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Biochemistry, Genetics & Molecular Biology Dentistry Health Professions Immunology & microbiology Medicine & Pharmacology

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Fungsi Pengunyahan dan Gangguan Kognitif  Terkait Kehilangan Gigi Pada Lansia Rani Rahayu, Elma; Asia, Rr. Asyurati; Ayu Ratih Utari Mayun, I Gusti
Jurnal Kedokteran Gigi Terpadu Vol. 7 No. 1 (2025): Jurnal Kedokteran Gigi Terpadu
Publisher : Fakultas Kedokteran Gigi Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jkgt.v7i1.23858

Abstract

Background: Aging causes various changes, including in the oral cavity tissues. The WHO recommends that elderly individuals aged ≥ 60 years should have at least 20 functional teeth to support their quality of life. Tooth loss in the elderly affects chewing function, psychological well-being, and cognitive function. Objectives: To determine the relationship between tooth loss in the elderly on masticatory function and cognitive impairment. Conclusion: Older adults with >12 missing teeth are more vulnerable to decreased masticatory function and cognitive impairment.
Peran Artificial Intelligence dalam Meningkatkan Akurasi Shade Guide di Kedokteran Gigi Estetik Nurkhansa Putri, Aisyah; Yuliani Taramalinda, Elizabeth; Rani Rahayu, Elma; Rainy Soenoe, Hanna; Safa Haniyah, Indira; Ardena Lianto Lie, Melisa; Octarina
Jurnal Kedokteran Gigi Terpadu Vol. 7 No. 2 (2025): Jurnal Kedokteran Gigi Terpadu
Publisher : Fakultas Kedokteran Gigi Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jkgt.v7i2.25995

Abstract

Background: Accurate tooth shade selection is a challenge in esthetic dentistry due to the subjectivity of visual methods and their sensitivity to environmental factors. Objectives: To examine the role of Artificial Intelligence (AI) in improving accuracy and the development of AI-based shade guide systems for tooth color determination. Methods: A literature review was conducted using data from several related studies. Results: AI and digital technology improve the accuracy and consistency of shade matching compared to conventional visual techniques. Deep learning models such as CNN, YOLO, and SegNet/U-Net enhance the precision of the process. AI also shortens clinical time and reduces dependence on human perception. However, its implementation faces challenges, including high costs, the need for large, high-quality datasets, and ethical concerns such as data privacy and informed consent. Conclusion: AI-assisted shade matching provides significant improvements in accuracy, consistency, and efficiency. To ensure successful clinical adoption, attention must be given to overcoming financial, data-related, and ethical barriers.
Co-Authors Ardena Lianto Lie, Melisa Asia, Rr. Asyurati I Gusti Ayu Ratih Utari Mayun Nurkhansa Putri, Aisyah Octarina Rainy Soenoe, Hanna Safa Haniyah, Indira Yuliani Taramalinda, Elizabeth