Singh Prabhat, Goyal Lokesh, Mallick Deobrat C, Surani Salim R, Kaushik Nayanjyoti, Chandramohan Deepak, Simhadri Prathap K
Department of Nephrology, Kidney Specialist of South Texas, Corpus Christi, TX.
Department of Internal Medicine, Christus Spohn Hospital, Corpus Christi, TX.
Kidney Med. 2024 Nov 12;7(1):100927. doi: 10.1016/j.xkme.2024.100927. eCollection 2025 Jan.
Artificial intelligence (AI) is increasingly used in many medical specialties. However, nephrology has lagged in adopting and incorporating machine learning techniques. Nephrology is well positioned to capitalize on the benefits of AI. The abundance of structured clinical data, combined with the mathematical nature of this specialty, makes it an attractive option for AI applications. AI can also play a significant role in addressing health inequities, especially in organ transplantation. It has also been used to detect rare diseases such as Fabry disease early. This review article aims to increase awareness on the basic concepts in machine learning and discuss AI applications in nephrology. It also addresses the challenges in integrating AI into clinical practice and the need for creating an AI-competent nephrology workforce. Even though AI will not replace nephrologists, those who are able to incorporate AI into their practice effectively will undoubtedly provide better care to their patients. The integration of AI technology is no longer just an option but a necessity for staying ahead in the field of nephrology. Finally, AI can contribute as a force multiplier in transitioning to a value-based care model.
人工智能（AI）在许多医学专科中的应用日益广泛。然而，肾脏病学在采用和整合机器学习技术方面却滞后了。肾脏病学具备充分利用人工智能优势的条件。丰富的结构化临床数据，再加上该专科的数学特性，使其成为人工智能应用的一个有吸引力的选择。人工智能在解决健康不平等问题，尤其是在器官移植方面，也能发挥重要作用。它还被用于早期检测诸如法布里病等罕见疾病。这篇综述文章旨在提高对机器学习基本概念的认识，并探讨人工智能在肾脏病学中的应用。它还阐述了将人工智能整合到临床实践中所面临的挑战，以及培养具备人工智能能力的肾脏病学专业人才的必要性。尽管人工智能不会取代肾脏病医生，但那些能够有效地将人工智能融入其临床实践的医生无疑将为患者提供更好的治疗。人工智能技术的整合不再只是一种选择，而是在肾脏病学领域保持领先地位的必要条件。最后，在向基于价值的医疗模式转变过程中，人工智能可以作为一种力量倍增器发挥作用。
