计算病理学是指将深度学习技术和算法应用于分析和解释组织病理学图像。人工智能（AI）的进步导致了计算病理学的创新爆发，从自动化常规诊断任务的可能性到从组织形态学中发现新的预后和预测生物标志物。尽管计算病理学具有很大的潜力，但其在临床环境中的整合受到一系列障碍的限制，包括操作、技术、监管、伦理、财务和文化方面的挑战。在这里，我们侧重于病理学家对计算病理学的看法：我们对其当前的转化研究领域进行了绘制，评估了其临床效用，并解决了减缓临床采用和实施的常见挑战。最后，我们描述了推动这些技术前进的现代方法。© 2023 The Authors. 《病理学杂志》由约翰·威利和儿子有限公司代表大不列颠和爱尔兰的病理学协会出版。

Computational pathology refers to applying deep learning techniques and algorithms to analyse and interpret histopathology images. Advances in artificial intelligence (AI) have led to an explosion in innovation in computational pathology, ranging from the prospect of automation of routine diagnostic tasks to the discovery of new prognostic and predictive biomarkers from tissue morphology. Despite the promising potential of computational pathology, its integration in clinical settings has been limited by a range of obstacles including operational, technical, regulatory, ethical, financial, and cultural challenges. Here, we focus on the pathologists' perspective of computational pathology: we map its current translational research landscape, evaluate its clinical utility, and address the more common challenges slowing clinical adoption and implementation. We conclude by describing contemporary approaches to drive forward these techniques. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.© 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.