Research Commons
      • Browse 
        • Communities & Collections
        • Titles
        • Authors
        • By Issue Date
        • Subjects
        • Types
        • Series
      • Help 
        • About
        • Collection Policy
        • OA Mandate Guidelines
        • Guidelines FAQ
        • Contact Us
      • My Account 
        • Sign In
        • Register
      View Item 
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computing and Mathematical Sciences Papers
      • View Item
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computing and Mathematical Sciences Papers
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Mobile support for diagnosis of communicable diseases in remote locations

      Cesario, Manuel; Lundon, Michael; Luz, Saturnino; Masoodian, Masood; Rogers, Bill
      DOI
       10.1145/2379256.2379261
      Find in your library  
      Citation
      Export citation
      Cesario, M., Lundon, M., Luz, S., Masoodian, M., & Rogers, B. (2012). Mobile support for diagnosis of communicable diseases in remote locations. In 13th International Conference of the NZ Chapter of the ACM's Special Interest Group on Human-Computer Interaction, CHINZ 2012, Dunedin, July 2-3 2012, (pp. 25-28). Dunedin, New Zealand.
      Permanent Research Commons link: https://hdl.handle.net/10289/6845
      Abstract
      Surveillance and diagnosis of new and emerging communicable diseases in remote regions, such as the Amazon, is a challenging task. These regions can be difficult to reach, are sparsely populated, and have limited medical and ICT infrastructure. Medical practitioners and community health agents who work in such regions often have very basic qualifications, and therefore have limited knowledge of new and emerging diseases. The increasing capabilities of mobile devices, such as tablets and smart phones, have made them a useful platform for delivery of medical services in remote locations. In this paper we introduce a system that could potentially support diagnosis of vector-borne diseases such as Bartonellosis and Leishmaniasis in areas where specialist healthcare is scarce. In particular, we focus on the image analysis and classification component of this system, which aims to reduce the chance of misdiagnosing these less common diseases as malaria.
      Date
      2012
      Type
      Conference Contribution
      Publisher
      ACM
      Collections
      • Computing and Mathematical Sciences Papers [1454]
      Show full item record  

      Usage

       
       
       

      Usage Statistics

      For this itemFor all of Research Commons

      The University of Waikato - Te Whare Wānanga o WaikatoFeedback and RequestsCopyright and Legal Statement