The Banff Digital Pathology Working Group (DPWG) was formed in the time leading up to and during the joint American Society for Histocompatibility and Immunogenetics/Banff Meeting, September 23‐27, 2019, held in Pittsburgh, Pennsylvania. At the meeting, the 14th Banff Conference, presentations directly and peripherally related to the topic of “digital pathology” were presented; and discussions before, during, and after the meeting have resulted in a list of issues to address for the DPWG. Included are practice standardization, integrative approaches for study classification, scoring of histologic parameters (eg, interstitial fibrosis and tubular atrophy and inflammation), algorithm classification, and precision diagnosis (eg, molecular pathways and therapeutics). Since the meeting, a survey with international participation of mostly pathologists (81%) was conducted, showing that whole slide imaging is available at the majority of centers (71%) but that artificial intelligence (AI)/machine learning was only used in ≈12% of centers, with a wide variety of programs/algorithms employed. Digitalization is not just an end in itself. It also is a necessary precondition for AI and other approaches. Discussions at the meeting and the survey highlight the unmet need for a Banff DPWG and point the way toward future contributions that can be made.

中文翻译：

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班夫数字病理学工作组：移植病理学走向数字化。

班夫数字病理学工作组 (DPWG) 成立于 2019 年 9 月 23 日至 27 日在宾夕法尼亚州匹兹堡举行的美国组织相容性和免疫遗传学协会/班夫联合会议之前和期间。在第 14 届班夫会议上，介绍了与“数字病理学”主题直接和外围相关的演讲；会前、会中和会后的讨论产生了 DPWG 需要解决的问题清单。包括实践标准化、研究分类的综合方法、组织学参数评分（例如，间质纤维化和肾小管萎缩和炎症）、算法分类和精确诊断（例如，分子途径和治疗）。自会议以来，进行了一项主要由病理学家 (81%) 参与的国际调查，表明大多数中心 (71%) 可以使用整个幻灯片成像，但人工智能 (AI)/机器学习仅在约 12% 的中心使用，使用了各种各样的程序/算法。数字化本身不仅仅是目的。这也是人工智能和其他方法的必要先决条件。会议上的讨论和调查突出了班夫 DPWG 未满足的需求，并指出了未来可以做出贡献的方式。这也是人工智能和其他方法的必要先决条件。会议上的讨论和调查突出了班夫 DPWG 未满足的需求，并指出了未来可以做出贡献的方式。这也是人工智能和其他方法的必要先决条件。会议上的讨论和调查突出了班夫 DPWG 未满足的需求，并指出了未来可以做出贡献的方式。