Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, Coventry, UK.
School of Computer Science, University of Birmingham, Birmingham, UK.
J Pathol. 2023 Aug;260(5):564-577. doi: 10.1002/path.6168. Epub 2023 Aug 7.
Computational pathology is currently witnessing a surge in the development of AI techniques, offering promise for achieving breakthroughs and significantly impacting the practices of pathology and oncology. These AI methods bring with them the potential to revolutionize diagnostic pipelines as well as treatment planning and overall patient care. Numerous peer-reviewed studies reporting remarkable performance across diverse tasks serve as a testimony to the potential of AI in the field. However, widespread adoption of these methods in clinical and pre-clinical settings still remains a challenge. In this review article, we present a detailed analysis of the major obstacles encountered during the development of effective models and their deployment in practice. We aim to provide readers with an overview of the latest developments, assist them with insights into identifying some specific challenges that may require resolution, and suggest recommendations and potential future research directions. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
计算病理学目前正见证着人工智能技术的飞速发展,有望实现突破,并对病理学和肿瘤学的实践产生重大影响。这些 AI 方法具有彻底改变诊断流程以及治疗计划和整体患者护理的潜力。大量经过同行评审的研究报告显示,AI 在各个领域的表现都非常出色,这证明了 AI 在该领域的潜力。然而,这些方法在临床和临床前环境中的广泛应用仍然是一个挑战。在这篇综述文章中,我们详细分析了在开发有效模型及其在实践中的部署过程中遇到的主要障碍。我们旨在为读者提供最新发展的概述,帮助他们了解可能需要解决的一些具体挑战,并提出建议和潜在的未来研究方向。© 2023 作者。《病理学杂志》由 John Wiley & Sons Ltd 代表大不列颠及爱尔兰病理学学会出版。