| 机器学习在肾病综合征患者他克莫司个体化用药中的应用 |
| 投稿时间：2023-10-08 修订日期：2024-03-19 点此下载全文 |
| 引用本文：丁千雪,尚圣兰,余梦辰,余爱荣.机器学习在肾病综合征患者他克莫司个体化用药中的应用[J].药学实践杂志,2024,42(6):227~230,243 |
| 摘要点击次数: 263 |
| 全文下载次数: 347 |
|
| 基金项目:中国博士后科学基金（2022M713859）；中部战区总医院博士后科研启动基金（20211227KY22） |
|
| 中文摘要:他克莫司是治疗肾病综合征的常用药物，因其治疗窗窄、药动学个体差异大，临床用药时需进行治疗药物监测。在治疗药物监测过程中，基于机器学习的他克莫司个体化用药预测模型可从大量临床数据中挖掘用药规律，辅助临床决策，实现个体化精准用药。本文围绕机器学习模型概述、机器学习在肾病综合征患者他克莫司个体化用药中的应用进展、机器学习预测模型的建模要点及当前预测模型的局限性等方面进行综述，以期为后续研究提供参考。 |
| 中文关键词:他克莫司 肾病综合征 机器学习 |
| |
| Application of machine learning in individualized medication of tacrolimus in patients with nephrotic syndrome |
|
|
| Abstract:Tacrolimus is a commonly used medication for the treatment of nephrotic syndrome. Due to its narrow therapeutic window and significant pharmacokinetic differences among individuals, therapeutic drug monitoring is required during its clinical use. In the process of therapeutic drug monitoring, machine learning-based personalized dosing prediction models for tacrolimus can excavate medication patterns from a large amount of clinical data, assist in clinical decision-making, and achieve individualized precise medication. Machine learning models, the application progress of machine learning in personalized administration of tacrolimus for patients with nephrotic syndrome, modeling points of machine learning prediction models, and the limitations of current prediction models were reviewed in this paper, which could provide references for future research in this field. |
| keywords:tacrolimus nephrotic syndrome machine learning |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
| 关闭 |
|
|
|
