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      Comparison of supervised machine learning algorithms for waterborne pathogen detection using mobile phone fluorescence microscopy

      , , , , ,
      Nanophotonics
      Walter de Gruyter GmbH

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          Abstract

          is a waterborne parasite that affects millions of people every year worldwide, causing a diarrheal illness known as giardiasis. Timely detection of the presence of the cysts of this parasite in drinking water is important to prevent the spread of the disease, especially in resource-limited settings. Here we provide extended experimental testing and evaluation of the performance and repeatability of a field-portable and cost-effective microscopy platform for automated detection and counting of

          Author and article information

          Journal
          Nanophotonics
          Walter de Gruyter GmbH
          2192-8614
          2192-8606
          January 27 2017
          January 14 2017
          January 1 2017
          January 27 2017
          January 14 2017
          January 1 2017
          : 6
          : 4
          Article
          10.1515/nanoph-2017-0001
          77379928-6c96-42cd-b014-9cf927897ad5
          © 2017

          http://creativecommons.org/licenses/by-nc-nd/3.0

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