The application of artificial intelligence to improve the access of cancer patients to high-quality medical care is one of the goals of modern medicine. Pathology constitutes the foundation of modern oncologic treatment, and its role has expanded far beyond diagnosis into predicting treatment response and overall survival. However, the funding of pathology is often an afterthought in resource-scarce medical systems. The increased digitalization of pathology has paved the way towards the potential use of artificial intelligence tools for improving pathologist efficiency and extracting more information from tissues. In this review, we provide an overview of the main research directions intersecting with artificial intelligence and pathology in relation to oncology, such as tumor classification, the prediction of molecular alterations, and biomarker quantification. We then discuss examples of tools that have matured into clinical products and gained regulatory approval for clinical use. Finally, we highlight the main hurdles that stand in the way of the digitalization of pathology and the application of artificial intelligence in pathology while also discussing possible solutions.
应用人工智能提升癌症患者获得高质量医疗服务的可及性，是现代医学的目标之一。病理学构成现代肿瘤治疗的基石，其作用已远超诊断范畴，延伸至预测治疗反应和总体生存期。然而在资源匮乏的医疗体系中，病理学科的资金支持常被忽视。病理学数字化进程的推进，为人工智能工具提升病理医生工作效率、从组织样本中提取更多信息创造了可能。本文综述了人工智能与肿瘤病理学交叉领域的主要研究方向，包括肿瘤分类、分子改变预测及生物标志物定量分析等。进而探讨已转化为临床产品并获得监管批准投入使用的工具实例。最后，我们重点剖析病理学数字化及人工智能应用面临的主要障碍，并对潜在解决方案展开讨论。
Breaking Barriers: AI’s Influence on Pathology and Oncology in Resource-Scarce Medical Systems
肿瘤(癌症)患者之家