Episode Summary

The European alchemists of the 12th century sought to find the philosopher’s stone, a substance that would transmute base metals, such as lead, into precious metals, such as silver and gold. Today, we discuss whether data analysis, including machine learning, can transmute base laboratory data into precious clinical tools. We will use antimicrobial susceptibility testing as a case-study for new applications of data analysis. Some of the questions we will address include:

  • How can relatively simple data analyses be used to build upon current methods of verification of antimicrobial susceptibility testing?
  • How do commercial systems analyze individual susceptibility results and can we improve on this analysis using new methods?
  • Finally, what is the long-term potential for leveraging laboratory data and other clinical data to improve and support clinical decision making? And what needs to happen to realize this goal?


Related article:

The modern alchemy of clinical pathology: turning the output of microbiology laboratory operations into gold


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This episode of Editors in Conversation is brought to you by the Journal of Clinical Microbiology and hosted by JCM Editor in Chief, Alex McAdam and Dr. Elli Theel. JCM is available at https://jcm.asm.org and on https://twitter.com/JClinMicro.

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