de Souza Lucas Lacerda, Fonseca Felipe Paiva, Araújo Anna Luiza Damaceno, Lopes Marcio Ajudarte, Vargas Pablo Agustin, Khurram Syed Ali, Kowalski Luiz Paulo, Dos Santos Harim Tavares, Warnakulasuriya Saman, Dolezal James, Pearson Alexander T, Santos-Silva Alan Roger
Oral Diagnosis, Piracicaba Dental School, University of Campinas (UNICAMP), São Paulo, Brazil.
Department of Oral Surgery and Pathology, School of Dentistry, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
J Oral Pathol Med. 2023 Mar;52(3):197-205. doi: 10.1111/jop.13414. Epub 2023 Mar 8.
Oral potentially malignant disorders represent precursor lesions that may undergo malignant transformation to oral cancer. There are many known risk factors associated with the development of oral potentially malignant disorders, and contribute to the risk of malignant transformation. Although many advances have been reported to understand the biological behavior of oral potentially malignant disorders, their clinical features that indicate the characteristics of malignant transformation are not well established. Early diagnosis of malignancy is the most important factor to improve patients' prognosis. The integration of machine learning into routine diagnosis has recently emerged as an adjunct to aid clinical examination. Increased performances of artificial intelligence AI-assisted medical devices are claimed to exceed the human capability in the clinical detection of early cancer. Therefore, the aim of this narrative review is to introduce artificial intelligence terminology, concepts, and models currently used in oncology to familiarize oral medicine scientists with the language skills, best research practices, and knowledge for developing machine learning models applied to the clinical detection of oral potentially malignant disorders.
口腔潜在恶性疾病代表可能会发生恶性转化成为口腔癌的前驱病变。有许多已知的与口腔潜在恶性疾病发生相关的风险因素，这些因素会增加恶性转化的风险。尽管已有许多进展被报道以了解口腔潜在恶性疾病的生物学行为，但其表明恶性转化特征的临床特征尚未完全明确。恶性肿瘤的早期诊断是改善患者预后的最重要因素。机器学习融入常规诊断最近已成为辅助临床检查的一种手段。据称，人工智能辅助医疗设备性能的提升使其在早期癌症临床检测方面超越了人类能力。因此，本叙述性综述的目的是介绍目前肿瘤学中使用的人工智能术语、概念和模型，以使口腔医学科学家熟悉用于开发应用于口腔潜在恶性疾病临床检测的机器学习模型的语言技能、最佳研究实践和知识。
