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  • 标题:Thermal mapp routing in pharmaceutical products transportation using machine learning approach: a systematic review
  • 本地全文:下载
  • 作者:Clayton Gerber Mangini ; Nilsa Duarte da Silva Lima ; Irenilza de Alencar Ns
  • 期刊名称:Research, Society and Development
  • 电子版ISSN:2525-3409
  • 出版年度:2021
  • 卷号:10
  • 期号:16
  • 页码:1-9
  • DOI:10.33448/rsd-v10i16.23665
  • 语种:English
  • 出版社:Grupo de Pesquisa Metodologias em Ensino e Aprendizagem em Ciências
  • 摘要:The cold chain is crucial to ensure the quality and effectiveness of transported and stored medicines. For this, it is necessary to carry out the thermal mapping of routes for drugs transported between 15°C and 30°C, so that the most assertive decision can be taken without raising costs. This study aims to identify the main factors influencing the thermal mapping of pharmaceutical products in the cold chain and applying the machine learning technique. The method used for this systematic review is the Prisma, where the identification, screening, eligibility, and inclusion stages were analyzed. After analyzing 75 articles, the result shows that only eight papers were consistent with the use of modeling in the medicine cold chain distribution. Thus, it can be concluded that there is an extensive field to be researched regarding the use of prediction algorithms in the cold chain of drugs and vaccines.
  • 关键词:Cold chain;Medicines;Vaccine;Modeling;Quality control.
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