在儿科急诊医学中通过人工智能解决方案进行个性化决策:专注于发烧儿童
Lina Jankauskaite1,2, Urte Oniunaite1, Rimantas Kevalas1
1Department of Pediatrics, Faculty of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania.
PLOS digital health
|November 3, 2025
概括
人工智能 (AI) 可以通过改进诊断和个性化治疗来增强儿科紧急医疗 (PEM). 解决数据挑战是彻底改变年轻患者护理的关键.
科学领域:
- 儿科急救医学 儿科急救医学
- 医疗保健中的人工智能
- 临床决策支持系统 临床决策支持系统
背景情况:
- 儿科紧急医疗 (PEM) 面临着独特的挑战,因为患者人群多样化和病例数量增加.
- 在儿科急诊室 (PED) 中,个性化决策和家庭提供者合作至关重要.
- 现有的方法需要改进,以管理复杂性并优化护理服务.
研究的目的:
- 审查人工智能 (AI) 在改变儿科紧急护理中的作用.
- 在PEM中分析AI应用在诊断辅助,预测建模和结果优化方面.
- 确定人工智能在儿科紧急情况中整合的挑战和机会.
主要方法:
- 在儿科急诊医学中对AI应用的文献综述.
- 分析AI在诊断准确性,治疗个性化和资源配置方面的潜力.
- 检查用于模式识别和早期疾病检测的机器学习算法.
主要成果:
- 人工智能可以提高诊断的准确性,并使用庞大的数据集来个性化治疗计划.
- 机器学习有助于在儿童患者的早期疾病检测和精确干预.
- 人工智能为优化资源配置和改善PED患者治疗结果提供了潜力.
结论:
- 人工智能集成具有显著的潜力,可以在儿科紧急情况下彻底改变个性化护理.
- 克服数据限制和确保算法透明度等挑战对于成功实施人工智能至关重要.
- 人工智能最终可以改善患者的治疗结果,并增强儿科急诊医学中的护理服务.
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