This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on chronic pulmonary aspergillosis and some supporting proof-of-concept results using lung imaging. Given the high uncertainty in fungal infection diagnosis and analyzing treatment response, AI could potentially have an impactful role; however, developing imaging-based machine learning raises several specific challenges. We discuss recommendations to engage the medical community in essential first steps towards fungal infection AI with gathering dedicated imaging registries, linking with non-imaging data and harmonizing image-finding annotations.

这篇定位论文旨在讨论人工智能 (AI) 在真菌性肺病中的当前挑战和机遇，重点关注慢性肺曲霉病和一些使用肺部成像的支持概念验证结果。鉴于真菌感染诊断和分析治疗反应的高度不确定性，人工智能可能会发挥重要作用；然而，开发基于成像的机器学习提出了几个具体的挑战。我们讨论了让医学界参与真菌感染 AI 的基本第一步的建议，包括收集专门的影像登记、与非影像数据联系并协调影像查找注释。