Цифровые технологии интеллектуальной идентификации личности в судебной медицине и стоматологии

В статье представлен литературный обзор публикаций, посвященных описанию современных методов цифровой идентификации личности с применением технологий искусственного интеллекта.

The article presents a literature review of publications devoted to the description of modern methods of digital identification of a person with the use of artificial intelligence technologies.

искусственный интеллект, судебная стоматология, идентификация личности.

artificial intelligence, forensic dentistry, personal identification, machine-aided training.

1. Долгалев А.А., Мураев А.А., Ляхов П.А., Ляхова У.А., Чониашвили Д.З., Золотаев К.Е., Семериков Д.Ю., Аванисян В.М. Архитектоника системы искусственного интеллекта и перспективы применения технологий машинного обучения в стоматологии. Обзор литературы // Главный врач юга России. - 2022. - № 5 (86). - С. 2-6.
2. Колесниченко О.Ю., Мартыненков А.В., Пулит В.В., Колесниченко Ю.Ю., Шакиров В.В., Мазелис Л.С., Варламов О.О., Минушкина Л.О., Сотник А.Ю., Жилина Т.Н., Дорофеев В.П., Смородин Г.Н., Жапаров М.К. Современный передовой уровень искусственного интеллекта для умной медицины // Ремедиум. - 2019. - № 4. - С. 36-43. DOI: https://doi.org/10.21518 / 1561-5936-2019-04-36-43.
3. Heinrich A, Güttler F, Wendt S, Schenkl S, Hubig M, Wagner R, et al. Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision // ROFO Fortschr Geb Rontgenstr Nuklearmed. - 2018. - № 190 (12): 1152-8.
4. Kaul B, Vaid V, Gupta S, Kaul S. Forensic Odontological Parameters as Biometric Tool: A Review // Int J Clin Pediatr Dent. - 2021. - № 14 (3): 416-9. DOI: 10.5005/jp-journals-10005-1967.
5. Kaya E, Gunec HG, Gokyay SS, Kutal S, Gulum S, Ates HF. Proposing a CNN Method for Primary and Permanent Tooth Detection and Enumeration on Pediatric Dental Radiographs // J Clin Pediatr Dent. - 2022. - № 46 (4): 293-8. DOI: 10.22514/1053-4625-46.4.6.
6. Marta Revilla-León, Miguel Gómez-Polo, Shantanu Vyas, Abdul Basir Barmak, Mutlu Özcan, Wael Att, Vinayak R Krishnamurthy. Artificial intelligence applications in restorative dentistry: A systematic review // J Prosthet Dent. - 2022. - № 128 (5): 867-875. DOI: 10.1016/j.prosdent.2021.02.010.
7. Milošević D, Vodanović M, Galić I, SubašIć M. A Comprehensive Exploration of Neural Networks for Forensic Analysis of Adult Single Tooth X-Ray Images // IEEE Access. - 2022. - № 10: 70980-1002. DOI: 10.1109/ACCESS.2022.3187959.
8. Seo H, Hwang J, Jung YH, Lee E, Nam OH, Shin J. Deep focus approach for accurate bone age estimation from lateral cephalogram // J Dent Sci. - 2023. - № 18 (1): 34-43. DOI: 10.1016/j.jds.2022.07.018.
9. Upalananda W, Wantanajittikul K, Na Lampang S, Janhom A. Semi-automated technique to assess the developmental stage of mandibular third molars for age estimation // Aust J Forensic Sci. - 2023. - № 55 (1): 23-33.
10. Vila-Blanco N, Varas-Quintana P, Aneiros-Ardao Á, Tomás I, Carreira MJ. Automated description of the mandible shape by deep learning // Int J Comput Assist Radiol Surg. - 2021. - № 16 (12): 2215-2224. DOI: 10.1007/s11548-021-02474-2.
11. Vodanović M, Subašić M, Milošević D, Savić Pavičin I. Artificial Intelligence in Medicine and Dentistry // Acta Stomatol Croat Int J Oral Sci Dent Med. - 2023. - № 57 (1): 70-84. doi: 10.15644/asc57/1/8.
12. Wuyang Shui, Xiujie Wu, Mingquan Zhou. A computerized facial approximation method for Homo sapiens based on facial soft tissue thickness depths and geometric morphometrics // Journal of Anatomy. - 2023. - № 243: 796-812. https://doi.org/10.1111/joa.13920.

REFERENCES:
1. Dolgalev A.A., Muraev A.A., Lyahov P.A., Lyahova U.A., CHoniashvili D.Z., Zolotaev K.E., Semerikov D.YU., Avanisyan V.M. Arhitektonika sistemy iskusstvennogo intellekta i perspektivy primeneniya tekhnologij mashinnogo obucheniya v stomatologii. Obzor literatury // Glavnyj vrach yuga Rossii. - 2022. - № 5 (86). - S. 2-6.
2. Kolesnichenko O.YU., Martynenkov A.V., Pulit V.V., Kolesnichenko YU.YU., SHakirov V.V., Mazelis L.S., Varlamov O.O., Minushkina L.O., Sotnik A.YU., ZHilina T.N., Dorofeev V.P., Smorodin G.N., ZHaparov M.K. Sovremennyj peredovoj uroven’ iskusstvennogo intellekta dlya umnoj mediciny // Remedium. - 2019. - № 4. - S. 36-43. DOI: https://doi.org/10.21518 / 1561-5936-2019-04-36-43.
3. Heinrich A, Güttler F, Wendt S, Schenkl S, Hubig M, Wagner R, et al. Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision // ROFO Fortschr Geb Rontgenstr Nuklearmed. - 2018. - № 190 (12): 1152-8.
4. Kaul B, Vaid V, Gupta S, Kaul S. Forensic Odontological Parameters as Biometric Tool: A Review // Int J Clin Pediatr Dent. - 2021. - № 14 (3): 416-9. DOI: 10.5005/jp-journals-10005-1967.
5. Kaya E, Gunec HG, Gokyay SS, Kutal S, Gulum S, Ates HF. Proposing a CNN Method for Primary and Permanent Tooth Detection and Enumeration on Pediatric Dental Radiographs // J Clin Pediatr Dent. - 2022. - № 46 (4): 293-8. DOI: 10.22514/1053-4625-46.4.6.
6. Marta Revilla-León, Miguel Gómez-Polo, Shantanu Vyas, Abdul Basir Barmak, Mutlu Özcan, Wael Att, Vinayak R Krishnamurthy. Artificial intelligence applications in restorative dentistry: A systematic review // J Prosthet Dent. - 2022. - № 128 (5): 867-875. DOI: 10.1016/j.prosdent.2021.02.010.
7. Milošević D, Vodanović M, Galić I, SubašIć M. A Comprehensive Exploration of Neural Networks for Forensic Analysis of Adult Single Tooth X-Ray Images // IEEE Access. - 2022. - № 10: 70980-1002. DOI: 10.1109/ACCESS.2022.3187959.
8. Seo H, Hwang J, Jung YH, Lee E, Nam OH, Shin J. Deep focus approach for accurate bone age estimation from lateral cephalogram // J Dent Sci. - 2023. - № 18 (1): 34-43. DOI: 10.1016/j.jds.2022.07.018.
9. Upalananda W, Wantanajittikul K, Na Lampang S, Janhom A. Semi-automated technique to assess the developmental stage of mandibular third molars for age estimation // Aust J Forensic Sci. - 2023. - № 55 (1): 23-33.
10. Vila-Blanco N, Varas-Quintana P, Aneiros-Ardao Á, Tomás I, Carreira MJ. Automated description of the mandible shape by deep learning // Int J Comput Assist Radiol Surg. - 2021. - № 16 (12): 2215-2224. DOI: 10.1007/s11548-021-02474-2.
11. Vodanović M, Subašić M, Milošević D, Savić Pavičin I. Artificial Intelligence in Medicine and Dentistry // Acta Stomatol Croat Int J Oral Sci Dent Med. - 2023. - № 57 (1): 70-84. doi: 10.15644/asc57/1/8.
12. Wuyang Shui, Xiujie Wu, Mingquan Zhou. A computerized facial approximation method for Homo sapiens based on facial soft tissue thickness depths and geometric morphometrics // Journal of Anatomy. - 2023. - № 243: 796-812. https://doi.org/10.1111/joa.13920.