Department of Medical Oncology, West China Hospital, Sichuan University, 610041, Chengdu, Sichuan Province, P. R. China.
Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, Sichuan Province, P. R. China.
Br J Cancer. 2023 Jun;128(12):2141-2149. doi: 10.1038/s41416-023-02215-z. Epub 2023 Mar 4.
Triple-negative breast cancer (TNBC) accounts for 15-20% of all invasive breast cancer subtypes. Owing to its clinical characteristics, such as the lack of effective therapeutic targets, high invasiveness, and high recurrence rate, TNBC is difficult to treat and has a poor prognosis. Currently, with the accumulation of large amounts of medical data and the development of computing technology, artificial intelligence (AI), particularly machine learning, has been applied to various aspects of TNBC research, including early screening, diagnosis, identification of molecular subtypes, personalised treatment, and prediction of prognosis and treatment response. In this review, we discussed the general principles of artificial intelligence, summarised its main applications in the diagnosis and treatment of TNBC, and provided new ideas and theoretical basis for the clinical diagnosis and treatment of TNBC.
三阴性乳腺癌（TNBC）占所有浸润性乳腺癌亚型的 15-20%。由于其临床特征，如缺乏有效的治疗靶点、侵袭性高和复发率高，TNBC 难以治疗，预后不良。目前，随着大量医疗数据的积累和计算技术的发展，人工智能（AI），特别是机器学习，已应用于 TNBC 研究的各个方面，包括早期筛查、诊断、分子亚型鉴定、个性化治疗以及预测预后和治疗反应。在这篇综述中，我们讨论了人工智能的一般原理，总结了其在 TNBC 诊断和治疗中的主要应用，并为 TNBC 的临床诊断和治疗提供了新的思路和理论依据。
