Nada Arwa, Ahmed Yamen, Hu Jieji, Weidemann Darcy, Gorman Gregory H, Lecea Eva Glenn, Sandokji Ibrahim A, Cha Stephen, Shin Stella, Bani-Hani Salar, Mannemuddhu Sai Sudha, Ruebner Rebecca L, Kakajiwala Aadil, Raina Rupesh, George Roshan, Elchaki Rim, Moritz Michael L
Department of Pediatrics, Division of Pediatric Nephrology, Loma Linda University Children's Hospital (LLUCH), Loma Linda University (LLU), 11175 Campus St. A1120H, Loma Linda, CA, 92350, USA.
Case Western Reserve University, Cleveland, OH, USA.
Pediatr Nephrol. 2025 Sep 16. doi: 10.1007/s00467-025-06911-1.
Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, therapeutic precision, and operational workflows. By integrating diverse datasets-including patient histories, genomics, imaging, and longitudinal clinical records-AI-driven tools can detect subtle kidney anomalies, predict acute kidney injury, and forecast disease progression. Deep learning models, for instance, have demonstrated the potential to enhance ultrasound interpretations, refine kidney biopsy assessments, and streamline pathology evaluations. Coupled with robust decision support systems, these innovations also optimize medication dosing and dialysis regimens, ultimately improving patient outcomes. AI-powered chatbots hold promise for improving patient engagement and adherence, while AI-assisted documentation solutions offer relief from administrative burdens, mitigating physician burnout. However, ethical and practical challenges remain. Healthcare professionals must receive adequate training to harness AI's capabilities, ensuring that such technologies bolster rather than erode the vital doctor-patient relationship. Safeguarding data privacy, minimizing algorithmic bias, and establishing standardized regulatory frameworks are critical for safe deployment. Beyond clinical care, AI can accelerate pediatric nephrology research by identifying biomarkers, enabling more precise patient recruitment, and uncovering novel therapeutic targets. As these tools evolve, interdisciplinary collaborations and ongoing oversight will be key to integrating AI responsibly. Harnessing AI's vast potential could revolutionize pediatric nephrology, championing a future of individualized, proactive, and empathetic care for children with kidney diseases. Through strategic collaboration and transparent development, these advanced technologies promise to minimize disparities, foster innovation, and sustain compassionate patient-centered care, shaping a new horizon in pediatric nephrology research and practice.
人工智能（AI）正在迅速成为儿科肾脏病学中一股变革性力量，能够提高诊断准确性、治疗精准度和优化操作流程。通过整合包括患者病史、基因组学、影像学和纵向临床记录等多种数据集，人工智能驱动的工具可以检测出细微的肾脏异常、预测急性肾损伤并预测疾病进展。例如，深度学习模型已显示出增强超声解读、完善肾活检评估以及简化病理评估的潜力。这些创新与强大的决策支持系统相结合，还能优化药物剂量和透析方案，最终改善患者预后。人工智能驱动的聊天机器人有望提高患者参与度和依从性，而人工智能辅助的文档解决方案则可减轻行政负担，缓解医生职业倦怠。然而，伦理和实际挑战依然存在。医疗保健专业人员必须接受充分培训以利用人工智能的能力，确保此类技术增强而非削弱至关重要的医患关系。保护数据隐私、最大限度减少算法偏差以及建立标准化监管框架对于安全部署至关重要。在临床护理之外，人工智能可以通过识别生物标志物、实现更精准的患者招募以及发现新的治疗靶点来加速儿科肾脏病学研究。随着这些工具的不断发展，跨学科合作和持续监督将是负责任地整合人工智能的关键。利用人工智能的巨大潜力可能会彻底改变儿科肾脏病学，为患有肾脏疾病的儿童开创一个个性化、积极主动且富有同情心的护理未来。通过战略合作和透明开发，这些先进技术有望最大限度减少差距、促进创新并维持以患者为中心的 compassionate 护理，塑造儿科肾脏病学研究与实践的新视野。 （注：compassionate 在这里可能是想表达“有同情心的”，推测可能是多打了个字母，正确的词应该是“compassionate”）
