Pereira-Prado Vanesa, Martins-Silveira Felipe, Sicco Estafanía, Hochmann Jimena, Isiordia-Espinoza Mario Alberto, González Rogelio González, Pandiar Deepak, Bologna-Molina Ronell
Molecular Pathology Area, School of Dentistry, Universidad de la República, Montevideo 11400, Uruguay.
Department of Clinics, Los Altos University Center, Institute of Research in Medical Sciences, University of Guadalajara, Guadalajara 44100, Mexico.
Diagnostics (Basel). 2023 Jul 20;13(14):2416. doi: 10.3390/diagnostics13142416.
Head and neck tumor differential diagnosis and prognosis have always been a challenge for oral pathologists due to their similarities and complexity. Artificial intelligence novel applications can function as an auxiliary tool for the objective interpretation of histomorphological digital slides. In this review, we present digital histopathological image analysis applications in oral squamous cell carcinoma. A literature search was performed in PubMed MEDLINE with the following keywords: "artificial intelligence" OR "deep learning" OR "machine learning" AND "oral squamous cell carcinoma". Artificial intelligence has proven to be a helpful tool in histopathological image analysis of tumors and other lesions, even though it is necessary to continue researching in this area, mainly for clinical validation.
头颈部肿瘤的鉴别诊断和预后一直是口腔病理学家面临的挑战，因为它们具有相似性和复杂性。人工智能的新应用可以作为一种辅助工具，用于对组织形态学数字切片进行客观解读。在本综述中，我们介绍了数字组织病理学图像分析在口腔鳞状细胞癌中的应用。我们在PubMed MEDLINE中进行了文献检索，关键词如下：“人工智能”或“深度学习”或“机器学习”以及“口腔鳞状细胞癌”。尽管在这一领域仍有必要继续开展研究，主要是进行临床验证，但人工智能已被证明是肿瘤和其他病变组织病理学图像分析中的一个有用工具。
