An ontology-based decision support system for nutrition deficiency

H. Tejaswini, M. M. Manohara Pai, Radhika M. Pai, Girija Attigeri, Revathi P. Shenoy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Storing the patient's clinical test reports for analysis differs from clinic to clinic as most clinics store the details in customized software or freely available spreadsheets. In the nutrition test report, the test results show the levels, thresholds that doctors analyze and diagnose the type of deficiency. In many situations, the patients have a dilemma about the doctor's advice that results in a second opinion. Hence a simple decision support system is a necessity to help the doctor to analyze the laboratory test report data and prescribe the right treatment. This research proposes a nutrition deficiency decision support framework that models a biochemistry test report using an ontology and automatic nutrition deficiency classification. The resulting system is useful in hospitals for the automatic classification of nutritional deficiency.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages267-272
Number of pages6
ISBN (Electronic)9781728198859
DOIs
Publication statusPublished - 30-10-2020
Event2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Udupi, India
Duration: 30-10-202031-10-2020

Publication series

Name2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings

Conference

Conference2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020
CountryIndia
CityUdupi
Period30-10-2031-10-20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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