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Study of Critical Vital Signs Using Deep Learning

  • Diego Felipe Rodríguez Chaparro
  • Octavio José Salcedo ParraEmail author
  • Erika Upegui
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10898)

Abstract

As the popularity of Deep Learning grows in the Science field, it is hard to avoid experiencing and discovering the scope of this powerful tool and all it has to offer. This work explores the possibility of using Deep Learning methodologies in the Medicine framework, oriented specifically to the study of vital signs from critical patients in the ER. Using a public domain dataset taken from Massachusetts General Hospital as well as the learning modules from Python, the objective is to use Deep Learning to calculate a patient’s chances of survival based on his vital signs.

Keywords

Deep learning Emergency room Keras Python Vital signs introduction 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Diego Felipe Rodríguez Chaparro
    • 1
  • Octavio José Salcedo Parra
    • 1
    • 2
    Email author
  • Erika Upegui
    • 3
  1. 1.Department of Systems and Industrial Engineering, Faculty of EngineeringUniversidad Nacional de ColombiaBogotá D.C.Colombia
  2. 2.Faculty of Engineering, Intelligent Internet Research GroupUniversidad Distrital “Francisco José de Caldas”Bogotá D.C.Colombia
  3. 3.Faculty of Engineering, GRSS-IEEE/UD & GEFEM Research GroupUniversidad Distrital “Francisco José de Caldas”Bogotá D.C.Colombia

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