Filler Guido, Gipson Debbie S, Iyamuremye Didier, Díaz González de Ferris Maria Esther
Division of Pediatric Nephrology, Departments of Paediatrics, Western University, London, Ontario, Canada; Departments of Medicine, Western University, London, Ontario, Canada; Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada.
Department of Pediatrics, University of Michigan, Ann Arbor, Michigan.
Adv Kidney Dis Health. 2023 Jan;30(1):17-24. doi: 10.1053/j.akdh.2022.11.001. Epub 2022 Dec 13.
Artificial intelligence is playing an increasingly important role in many fields of clinical care to assist health care providers in patient management. In adult-focused nephrology, artificial intelligence is beginning to be used to improve clinical care, hemodialysis prescriptions, and follow-up of transplant recipients. This article provides an overview of medical artificial intelligence applications relevant to pediatric nephrology. We describe the core concepts of artificial intelligence and machine learning and cover the basics of neural networks and deep learning. We also discuss some examples for clinical applications of artificial intelligence in pediatric nephrology, including neonatal kidney function, early recognition of acute kidney injury, renally cleared drug dosing, intrapatient variability, urinary tract infection workup in infancy, and longitudinal disease progression. Furthermore, we consider the future of artificial intelligence in clinical pediatric nephrology and its potential impact on medical practice and address the ethical issues artificial intelligence raises in terms of clinical decision-making, health care provider-patient relationship, patient privacy, and data collection. This article also represents a call for action involving those of us striving to provide optimal services for children, adolescents, and young adults with chronic conditions.
人工智能在临床护理的许多领域正发挥着越来越重要的作用,以协助医疗保健提供者进行患者管理。在以成人为主的肾脏病学中,人工智能正开始用于改善临床护理、血液透析处方以及移植受者的随访。本文概述了与儿科肾脏病学相关的医学人工智能应用。我们描述了人工智能和机器学习的核心概念,并涵盖神经网络和深度学习的基础知识。我们还讨论了人工智能在儿科肾脏病学临床应用的一些例子,包括新生儿肾功能、急性肾损伤的早期识别、经肾脏清除药物的剂量、患者个体差异、婴儿期尿路感染的检查以及疾病的纵向进展。此外,我们考虑了人工智能在临床儿科肾脏病学中的未来及其对医疗实践的潜在影响,并探讨了人工智能在临床决策、医疗保健提供者与患者关系、患者隐私和数据收集方面引发的伦理问题。本文也是呼吁我们这些努力为患有慢性病的儿童、青少年和年轻人提供最佳服务的人采取行动。