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Towards Knowledge-Driven Symptom Monitoring & Trigger Detection of Primary Headache Disorders

Authors:

Mathias De Brouwer,

Nicolas Vandenbussche,

Bram Steenwinckel,

Marija Stojchevska,

Jonas Van Der Donckt,

Femke OngenaeAuthors Info & Claims

WWW '22: Companion Proceedings of the Web Conference 2022

Pages 264 - 268

https://doi.org/10.1145/3487553.3524256

Published: 16 August 2022 Publication History

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Abstract

Headache disorders are experienced by many people around the world. In current clinical practice, the follow-up and diagnosis of headache disorder patients only happens intermittently, based on subjective data self-reported by the patient. The mBrain system tries to make this process more continuous, autonomous and objective by additionally collecting contextual and physiological data via a wearable, mobile app and machine learning algorithms. To support the monitoring of headache symptoms during attacks for headache classification and the detection of headache triggers, much knowledge and contextual data is available from heterogeneous sources, which can be consolidated with semantics. This paper presents a demonstrator of knowledge-driven services that perform these tasks using Semantic Web technologies. These services are deployed in a distributed cascading architecture that includes DIVIDE to derive and manage the RDF stream processing queries that perform the contextually relevant filtering in an intelligent and efficient way.

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Cited By

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Bonte POngenae FTommasini R(2024)A holistic view over ontologies for Streaming Linked DataSemantic Web10.3233/SW-243570(1-29)Online publication date: 6-Aug-2024
https://doi.org/10.3233/SW-243570
Belani HSolic PPerkovic T(2022)An Industrial IoT-Based Ontology Development for Well-Being, Aging and Health: A Scoping Review2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)10.1109/HealthCom54947.2022.9982769(179-185)Online publication date: 17-Oct-2022
https://doi.org/10.1109/HealthCom54947.2022.9982769

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Towards Knowledge-Driven Symptom Monitoring & Trigger Detection of Primary Headache Disorders

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Published In

WWW '22: Companion Proceedings of the Web Conference 2022

April 2022

1338 pages

ISBN:9781450391306

DOI:10.1145/3487553

Editors:
Frédérique Laforest
INSA Lyon, France
,
Raphaël Troncy
EURECOM, France
,
Lionel Médini
Université Lyon 1, France
,
Ivan Herman
W3C / retired

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 August 2022

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Fonds Wetenschappelijk Onderzoek
Fonds voor Innovatie en Klinisch Onderzoek, UZ Gent

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WWW '22

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SIGWEB

WWW '22: The ACM Web Conference 2022

April 25 - 29, 2022

Virtual Event, Lyon, France

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Bonte POngenae FTommasini R(2024)A holistic view over ontologies for Streaming Linked DataSemantic Web10.3233/SW-243570(1-29)Online publication date: 6-Aug-2024
https://doi.org/10.3233/SW-243570
Belani HSolic PPerkovic T(2022)An Industrial IoT-Based Ontology Development for Well-Being, Aging and Health: A Scoping Review2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom)10.1109/HealthCom54947.2022.9982769(179-185)Online publication date: 17-Oct-2022
https://doi.org/10.1109/HealthCom54947.2022.9982769

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Recommendations

Protocol-Driven Decision Support within e-Referral Systems to Streamline Patient Consultation, Triaging and Referrals from Primary Care to Specialist Clinics

A Hybrid Bio-inspired Clustering Approach for Diagnosing Children with Primary Headache Disorder

Knowledge-Driven diagnostic system for traditional chinese medicine

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