Application of Artificial Intelligence in Oral Cavity Cancer: A Review
Author:
Funder
Dong-A University
Publisher
The Busan, Ulsan, Gyeoungnam Branch of The Korean Society of Otolaryngology
Subject
General Medicine
Link
http://www.jcohns.org/download/download_pdf?doi=10.35420/jcohns.2023.34.2.23
Reference7 articles.
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2. Elmakaty I, Elmarasi M, Amarah A, Abdo R, Malki MI. Accuracy of artificial intelligence-assisted detection of oral squamous cell carcinoma: a systematic review and meta-analysis. Crit Rev Oncol Hematol 2022;178: 103777. 10.1016/j.critrevonc.2022.103777 35931404
3. Kim JS, Kim BG, Hwang SH. Efficacy of artificial intelligence-assisted discrimination of oral cancerous lesions from normal mucosa based on the oral mucosal image: a systematic review and meta-analysis. Cancers (Basel) 2022;14(14):3499. 10.3390/cancers14143499 35884560 PMC9320189
4. Chiesa-Estomba CM, Graña M, Medela A, Sistiaga-Suarez JA, Lechien JR, Calvo-Henriquez C, et al. Machine learning algorithms as a computer-assisted decision tool for oral cancer prognosis and management decisions: a systematic review. ORL J Otorhinolaryngol Relat Spec 2022;84(4):278-88. 10.1159/000520672 35021182
5. Adeoye J, Tan JY, Choi SW, Thomson P. Prediction models applying machine learning to oral cavity cancer outcomes: a systematic review. Int J Med Inform 2021; 154:104557. 10.1016/j.ijmedinf.2021.104557 34455119
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