A clinical decision support system based on an unobtrusive mobile app

Ariella Richardson, Avigail Perl, Sapir Natan, Gil Segev

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Clinical decision support systems typically rely on medical records and information collected in the doctor's office. We propose a clinical decision support system that uses data collected from patients continuously and in an unobtrusive manner. The system uses data collected from a mobile app installed on the patient's device (such as a mobile phone, smart-watch etc). The app collects data without user interference and combines it with conventional medical records. Our system uses machine learning methods to extract meaningful insights from the data. The output from the learning process is then presented to the doctor in a clear and meaningful fashion on a web based platform. This system can be used to assist effective treatment selection, enable early diagnosis, trigger alarms in case of an emergency and provide a tool for disease monitoring. We describe our clinical decision support system and directions for future work.

Original languageAmerican English
Title of host publicationICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health
EditorsMartina Ziefle, Leszek Maciaszek
Pages167-173
Number of pages7
ISBN (Electronic)9789897583681
DOIs
StatePublished - 2019
Externally publishedYes
Event5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019 - Heraklion, Crete, Greece
Duration: 2 May 20194 May 2019

Publication series

NameICT4AWE 2019 - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

Conference

Conference5th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2019
Country/TerritoryGreece
CityHeraklion, Crete
Period2/05/194/05/19

Keywords

  • Cardiovascular Disease
  • Clinical Decision Support System (CDSS)
  • Digital Health
  • Digital Monitoring
  • Medical Decision Support System (MDSS)
  • Mobile Health
  • Silent Disease

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Health Informatics

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