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Updated: Jan 8, 2026

Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics
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使用统计和机器学习模型对抗生素耐药性趋势的全球预测:通过中断时间序列分析评估国家行动计划的政策影响

Linta Khalid1, Kashif Saleem2, Saima Mushtaq3

  • 1School of Interdisciplinary Engineering & Science (SINES), National University of Sciences & Technology (NUST), H12, Islamabad, 44000, Pakistan; Department of Pharmacy Administration, School of Pharmacy, Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Journal of global antimicrobial resistance
|December 20, 2025
PubMed
概括

在全球范围内,抗菌素耐药性 (AMR) 正在上升,特别是在低收入国家. 这项研究提供了一个数据驱动的框架,用于追踪AMR的传播,预测未来的趋势,并为不同地区和收入群体提供针对性的干预措施.

关键词:
这种细菌是Acinetobacter baumannii.抗微生物耐药性 (AMR) 是一种预测 预测 预测 预测间断时间序列 (ITS)国家行动计划 (NAP)政策评估 政策评估维维利的AMR是一种AMR.

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