Xuanwu Hospital, Capital Medical University
垂体腺瘤（pituitary adenoma, PA）是一种起源于鞍区常见的良性肿瘤。随着检查技术的发展，其发病率逐年升高。又由于PA的临床表现丰富、病理类型多样，相应的治疗手段不同，导致相关的研究数据复杂。同时其诊治方案的选择及预后主要依靠医师的临床经验，给PA的相关研究带来了巨大挑战。机器学习作为人工智能领域的一种新的研究方法，可做到数据的深度发掘与分类，使预测结果的准确性得以提高，为治疗及预后的判断提供了有力帮助。本文就近年来机器学习在PA诊疗中的应用进展作一综述。
Pituitary adenoma (PA) is a common benign tumor arising from the sellar region. With the development of the examination technique, its incidence rate is increasing every year. Because of various clinical presentations, pathologic types and therapeutic approaches, there are complex data to research. What’s more, previous diagnosis and treatment methods of PA are mainly based on the clinical experience of doctors, which brings great challenges to related research. Machine learning, a new research method in the field of artificial intelligence, can achieve in-depth data mining and classification. This approach can improve the accuracy of results and aid diagnosis, treatment, and prediction of prognosis. Here we review the application of machine learning in the diagnosis and treatment of PA.