پیوندهای مفید
آمار
| تعداد نشریات | 20 |
| تعداد شماره‌ها | 1,149 |
| تعداد مقالات | 10,518 |
| تعداد مشاهده مقاله | 45,415,564 |
| تعداد دریافت فایل اصل مقاله | 11,291,386 |
Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation | ||
| Journal of Dentistry | ||
| مقاله 1، دوره 25، شماره 2 - شماره پیاپی 83، شهریور 2024، صفحه 95-96 اصل مقاله (99.98 K) | ||
| نوع مقاله: Letter to Editor | ||
| شناسه دیجیتال (DOI): 10.30476/dentjods.2024.101237.2284 | ||
| نویسندگان | ||
| Mohammad Reza Golzar Feshalami1؛ Mehraban Shahi2؛ Nasrin Davaridolatabadi* 2 | ||
| 1Student Research Committee, Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran. | ||
| 2Dept. of Health Information Management, Dept. of Health Information Technology, School of Allied Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, Iran. | ||
| چکیده | ||
| The advancement of artificial intelligence (AI) has opened up new possibilities for medical diagnosis and treatment. In particular, AI algorithms have demonstrated remarkable potential in analyzing patient radiology images and histopathological samples, offering insights that can enhance clinical decision-making [1]. This letter explores the emerging role of AI in the diagnosis and treatment of odontogenic tumors (OTs), a group of benign, malignant, and tumor-like malformations arising from the remnants of the tooth-forming apparatus. | ||
تازه های تحقیق | ||
Nasrin Davaridolatabadi (google scholar) | ||
| کلیدواژه‌ها | ||
| Artificial intelligence؛ Cone-Beam Computed Tomography؛ Odontogenic tumors | ||
|
سایر فایل های مرتبط با مقاله
|
||
| مراجع | ||
|
[1] Majumder A, Sen D. Artificial intelligence in cancer diagnostics and therapy: current perspectives. Indian J Cancer. 2021; 58: 481-492.
[2] Nalabolu GRK, Mohiddin A, Hiremath SKS, Manyam R, Bharath TS, Raju PR. Epidemiological study of odontogenic tumours: An institutional experience. J Infect Public Health. 2017; 10: 324-330.
[3] Chai ZK, Mao L, Chen H, Sun TG, Shen XM, Liu J, et al. Improved diagnostic accuracy of ameloblastoma and odontogenic keratocyst on cone-beam CT by artificial intelligence. Front Oncol. 2021; 11: 793417.
[4] Lee JH, Kim DH, Jeong SN. Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network. Oral Dis. 2020; 26: 152-158.
[5] Motie P, Hemmati G, Hazrati P, Lazar M, Varzaneh FA, Mohammad-Rahimi H, et al. Application of artificial intelligence in diagnosing oral and maxillofacial lesions, facial corrective surgeries, and maxillofacial reconstructive procedures. In: Khojasteh A, Ayoub AF, Nadjmi N, editors. Emerging Technologies in Oral and Maxillofacial Surgery. 1th ed. Singapore: Springer Nature Singapore; 2023. p. 287-328.
[6] Cai X, Zhang H, Wang Y, Zhang J, Li T. Digital pathology-based artificial intelligence models for differential diagnosis and prognosis of sporadic odontogenic keratocysts. Int J Oral Sci. 2024; 16: 16.
[7] Giraldo-Roldan D, Ribeiro ECC, Araújo ALD, Penafort PVM, Silva VMD, Câmara J, et al. Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas. J Oral Pathol Med. 2023; 52: 988-995.
[8] Zhong NN, Wang HQ, Huang XY, Li ZZ, Cao LM, Huo FY, et al. Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives. Semin Cancer Biol. 2023; 95: 52-74.
[9] Miragall MF, Knoedler S, Kauke-Navarro M, Saadoun R, Grabenhorst A, Grill FD, et al. Face the future- artificial intelligence in oral and maxillofacial surgery. J Clin Med. 2023; 12: 6843.
[10] Kawakami H, Suenaga H, Sakakibara A, Hoshi K. Computer-assisted surgery with markerless augmented reality for the surgical removal of mandibular odontogenic cysts: report of two clinical cases. Int J Oral Maxillofac Surg. 2024; 53: 347-350. | ||
|
آمار تعداد مشاهده مقاله: 369 تعداد دریافت فایل اصل مقاله: 338 |
||
