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提高末期病结果预测:一种多源数据驱动的方法

Yubo Li1, Rema Padman1

  • 1Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213, United States.

Journal of the American Medical Informatics Association : JAMIA
|August 12, 2025
PubMed
概括

通过将临床和索赔数据与机器学习模型相结合,可以更好地预测慢性病 (CKD) 到末期病 (ESRD) 的进展. 可解释的人工智能提高了解释性,减少了偏见,有助于更好地管理患者.

关键词:
慢性脏疾病 慢性脏疾病临床和索赔数据的整合.最终阶段的脏疾病.机器学习是机器学习.预测建模预测建模

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