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Authors: Ariella Richardson 1 ; Avigail Perl 1 ; Sapir Natan 1 and Gil Segev 2

Affiliations: 1 Lev Academic Center, Jerusalem and Israel ; 2 BGSegev Ltd. (segevlabs.org), Jerusalem and Israel

Keyword(s): Mobile Health, Digital Health, Digital Monitoring, Clinical Decision Support System (CDSS), Medical Decision Support System (MDSS), Cardiovascular Disease, Silent Disease.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Knowledge-Based Systems ; Symbolic Systems

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Richardson, A.; Perl, A.; Natan, S. and Segev, G. (2019). A Clinical Decision Support System based on an Unobtrusive Mobile App. In Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE; ISBN 978-989-758-368-1; ISSN 2184-4992, SciTePress, pages 167-173. DOI: 10.5220/0007587001670173

@conference{ict4awe19,
author={Ariella Richardson. and Avigail Perl. and Sapir Natan. and Gil Segev.},
title={A Clinical Decision Support System based on an Unobtrusive Mobile App},
booktitle={Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE},
year={2019},
pages={167-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007587001670173},
isbn={978-989-758-368-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE
TI - A Clinical Decision Support System based on an Unobtrusive Mobile App
SN - 978-989-758-368-1
IS - 2184-4992
AU - Richardson, A.
AU - Perl, A.
AU - Natan, S.
AU - Segev, G.
PY - 2019
SP - 167
EP - 173
DO - 10.5220/0007587001670173
PB - SciTePress