Artificial Intelligence in Nephrology: Clinical Applications and Challenges

IF 3.4 Q1 UROLOGY & NEPHROLOGY Kidney Medicine Pub Date : 2025-01-01 DOI:10.1016/j.xkme.2024.100927
Prabhat Singh , Lokesh Goyal , Deobrat C. Mallick , Salim R. Surani , Nayanjyoti Kaushik , Deepak Chandramohan , Prathap K. Simhadri
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Abstract

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.

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人工智能在肾脏病学中的临床应用和挑战。
人工智能(AI)越来越多地应用于许多医学专业。然而,肾脏病学在采用和融入机器学习技术方面却相对滞后。肾脏病学完全有能力利用人工智能的优势。大量的结构化临床数据加上该专业的数学性质,使其成为人工智能应用的一个有吸引力的选择。人工智能还能在解决健康不公平方面发挥重要作用,尤其是在器官移植方面。它还被用于早期检测法布里病等罕见疾病。这篇综述文章旨在提高人们对机器学习基本概念的认识,并讨论人工智能在肾脏病学中的应用。文章还探讨了将人工智能融入临床实践所面临的挑战,以及建立一支具备人工智能能力的肾脏病学人才队伍的必要性。尽管人工智能不会取代肾脏病学家,但那些能够将人工智能有效融入临床实践的肾脏病学家无疑将为患者提供更好的护理。整合人工智能技术不再只是一种选择,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过渡的过程中,人工智能可以起到事半功倍的作用。
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来源期刊
Kidney Medicine
Kidney Medicine Medicine-Internal Medicine
CiteScore
4.80
自引率
5.10%
发文量
176
审稿时长
12 weeks
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