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<p>This perspective discusses the present and future role of artificial intelligence (AI) and machine learning (ML) in surface-enhanced Raman scattering (SERS) sensing. Our goal is to guide the reader through current applications, mainly focused on discriminative approaches aimed at developing new and improved SERS diagnostic capabilities, towards the future role of AI in SERS sensing, with the use of generative approaches to design new materials and biomaterials.</p>

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AI in SERS sensing moving from discriminative to generative

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月21日

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  • Steven M. Quarin,
  • Der Vang,
  • Ruxandra I. Dima,
  • George Stan,
  • Pietro Strobbia

摘要

This perspective discusses the present and future role of artificial intelligence (AI) and machine learning (ML) in surface-enhanced Raman scattering (SERS) sensing. Our goal is to guide the reader through current applications, mainly focused on discriminative approaches aimed at developing new and improved SERS diagnostic capabilities, towards the future role of AI in SERS sensing, with the use of generative approaches to design new materials and biomaterials.