Mr. Silva and Patient Zero: A Medical Social Network and Data Visualization Information System

  • Patrícia C. T. GonçalvesEmail author
  • Ana S. Moura
  • M. Natália D. S. Cordeiro
  • Pedro Campos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11042)


Detection of Patient Zero is an increasing concern in a world where fast international transports makes pandemia a Public Health issue and a social fear, in cases such as Ebola or H5N1. The development of a medical social network and data visualization information system, which would work as an interface between the patient medical data and geographical and/or social connections, could be an interesting solution, as it would allow to quickly evaluate not only individuals at risk but also the prospective geographical areas for imminent contagion. In this work we propose an ideal model, and contrast it with the status quo of present medical social networks, within the context of medical data visualization. From recent publications, it is clear that our model converges with the identified aspects of prospective medical networks, though data protection is a key concern and implementation would have to seriously consider it.


Medical social networks Data visualization Epidemiology 



Patrícia C. T. Gonçalves and Pedro Campos would like to thank the European Regional Development Fund (ERDF) through the COMPETE 2020 Programme, project POCI-01-0145-FEDER-006961, and the National Funds through the Fundação para a Ciência e a Tecnologia (FCT) as part of project UID/EEA/50014/2013. Ana S. Moura and M. Natalia D.S. Cordeiro acknowledge the support by Fundação para a Ciência e a Tecnologia (FCT/MEC) through national funds and co-financed by FEDER, under the partnership agreement PT2020 (Projects UID/MULTI/50006 and POCI-01-0145-FEDER-007265).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Patrícia C. T. Gonçalves
    • 1
    • 2
    Email author
  • Ana S. Moura
    • 3
  • M. Natália D. S. Cordeiro
    • 3
  • Pedro Campos
    • 1
    • 4
  1. 1.LIAAD - Laboratório de Inteligência Artificial e Apoio à DecisãoINESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e CiênciaPortoPortugal
  2. 2.Departamento de Engenharia e Gestão industrial, Faculdade de EngenhariaUniversidade do PortoPortoPortugal
  3. 3.LAQV-REQUIMTE, Departamento de Química e Bioquímica, Faculdade de CiênciasUniversidade do PortoPortoPortugal
  4. 4.Departamento de Matemática e Sistemas de Informação, Faculdade de EconomiaUniversidade do PortoPortoPortugal

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