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Author Van Echelpoel, R.; de Jong, M.; Daems, D.; van Espen, P.; De Wael, K. pdf  url
doi  openurl
  Title Unlocking the full potential of voltammetric data analysis : a novel peak recognition approach for (bio)analytical applications Type A1 Journal article
  Year (down) 2021 Publication Talanta Abbreviated Journal Talanta  
  Volume 233 Issue Pages 122605  
  Keywords A1 Journal article; Engineering sciences. Technology; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)  
  Abstract Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 000668000500108 Publication Date 2021-06-11  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0039-9140; 1873-3573 ISBN Additional Links UA library record; WoS full record; WoS citing articles  
  Impact Factor 4.162 Times cited Open Access OpenAccess  
  Notes Approved Most recent IF: 4.162  
  Call Number UA @ admin @ c:irua:179417 Serial 8712  
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