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移植病理学中的人工智能进展

Artificial Intelligence Advances in Transplant Pathology.

作者信息

Rahman Md Arafatur, Yilmaz Ibrahim, Albadri Sam T, Salem Fadi E, Dangott Bryan J, Taner C Burcin, Nassar Aziza, Akkus Zeynettin

机构信息

Department of Laboratory Medicine and Pathology, Mayo Clinic, Jacksonville, FL 32224, USA.

Department of Mathematics, Florida State University, Tallahassee, FL 32306, USA.

出版信息

Bioengineering (Basel). 2023 Sep 4;10(9):1041. doi: 10.3390/bioengineering10091041.

Abstract

Transplant pathology plays a critical role in ensuring that transplanted organs function properly and the immune systems of the recipients do not reject them. To improve outcomes for transplant recipients, accurate diagnosis and timely treatment are essential. Recent advances in artificial intelligence (AI)-empowered digital pathology could help monitor allograft rejection and weaning of immunosuppressive drugs. To explore the role of AI in transplant pathology, we conducted a systematic search of electronic databases from January 2010 to April 2023. The PRISMA checklist was used as a guide for screening article titles, abstracts, and full texts, and we selected articles that met our inclusion criteria. Through this search, we identified 68 articles from multiple databases. After careful screening, only 14 articles were included based on title and abstract. Our review focuses on the AI approaches applied to four transplant organs: heart, lungs, liver, and kidneys. Specifically, we found that several deep learning-based AI models have been developed to analyze digital pathology slides of biopsy specimens from transplant organs. The use of AI models could improve clinicians' decision-making capabilities and reduce diagnostic variability. In conclusion, our review highlights the advancements and limitations of AI in transplant pathology. We believe that these AI technologies have the potential to significantly improve transplant outcomes and pave the way for future advancements in this field.

摘要

移植病理学在确保移植器官正常运作以及受体免疫系统不排斥这些器官方面发挥着关键作用。为了改善移植受体的预后,准确诊断和及时治疗至关重要。人工智能赋能的数字病理学的最新进展有助于监测同种异体移植排斥反应和免疫抑制药物的撤减。为了探究人工智能在移植病理学中的作用,我们对2010年1月至2023年4月的电子数据库进行了系统检索。PRISMA清单被用作筛选文章标题、摘要和全文的指南,我们选择了符合纳入标准的文章。通过这次检索,我们从多个数据库中识别出68篇文章。经过仔细筛选,基于标题和摘要仅纳入了14篇文章。我们的综述聚焦于应用于四种移植器官(心脏、肺、肝脏和肾脏)的人工智能方法。具体而言,我们发现已经开发了几种基于深度学习的人工智能模型来分析来自移植器官活检标本的数字病理切片。人工智能模型的使用可以提高临床医生的决策能力并减少诊断变异性。总之,我们的综述突出了人工智能在移植病理学中的进展和局限性。我们相信这些人工智能技术有潜力显著改善移植预后,并为该领域的未来进展铺平道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22e2/10525684/875751de28a9/bioengineering-10-01041-g001.jpg

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