Abstract：
Artificial intelligence (AI) and machine learning (ML) research within medicine has exponentially increased over the last decade, with studies showcasing the potential of AI/ML algorithms to improve clinical practice and outcomes. Ongoing research and efforts to develop AI-based models have expanded to aid in the identification of inborn errors of immunity (IEI). The use of larger electronic health record data sets, coupled with advances in phenotyping precision and enhancements in ML techniques, has the potential to significantly improve the early recognition of IEI, thereby increasing access to equitable care. In this review, we provide a comprehensive examination of AI/ML for IEI, covering the spectrum from data preprocessing for AI/ML analysis to current applications within immunology, and address the challenges associated with implementing clinical decision support systems to refine the diagnosis and management of IEI.
摘要：
在过去的十年中，医学领域的人工智能（AI）和机器学习（ML）研究呈指数增长。研究展示了AI/ML算法改善临床实践和结果的潜力。正在进行的研究和开发基于AI的模型的努力已经扩展到有助于识别先天性免疫错误(IEI)。利用更大的电子健康记录(EHR)数据集，再加上表型精度的进步和ML技术的增强，有可能显著提高对IEI的早期认识，从而增加获得公平护理的机会。在这次审查中,我们为IEI提供AI/ML的全面检查，涵盖从AI/ML分析的数据预处理到免疫学中的当前应用的范围，并解决与实施临床决策支持系统（CDSS）以完善IEI的诊断和管理相关的挑战。
