Appraisal of Artificial Intelligence for fall prevention & fall risk assessment
2022 (English) In: Proceedings of the 5th International Conference on Informatics & Data-Driven MedicineLyon, France, November 18 - 20, 2022 / [ed] Shakhovska N., Chretien S., Izonin I., Campos J., CEUR-WS , 2022, Vol. 3302, p. 21-34Conference paper, Published paper (Refereed)
Abstract [en]
The current article highlights the specific challenges and issues of the healthcare system in Europe. In addition, the particular factors towards the digitalization of the domain are highlighted, and the emerging technologies contribute to this process because many things are becoming more feasible. Thus, information and communication technologies (ICTs), such as new sensors, machine learning, big data, and analytics, provide new opportunities and challenges in their implementation and use. Therefore, it has become crucial to understand the different kinds of ICTs, such as artificial intelligence (A.I) techniques, especially machine learning algorithms and their use in the domain of interest. Thus, the paper aims to understand the mentioned technologies and their implementation in the area of interest to comprehend their current status, their suitability, and what needs to be considered for their successful development and implementation. While at the same time taking into account several key aspects that need to be well-thought-out in the domain. Consequently, the author performs a conceptual literature review of relevant scientific articles where sensors, machine learning, data mining, statistical learning, etc., have been tested and utilized in the eHealth area, especially for fall prevention and fall risk assessment. Finally, the literature findings are discussed, and the factors to consider when applying machine learning for fall prevention and fall risk assessment are underscored. © 2022 Copyright for this paper by its authors.
Place, publisher, year, edition, pages CEUR-WS , 2022. Vol. 3302, p. 21-34
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 3302
Keywords [en]
Accident prevention, Data mining, eHealth, Learning algorithms, Machine learning, ’current, Ehealth, Emerging technologies, Fall prevention, Fall risk, Fall risk assessment, Healthcare systems, Information and Communication Technologies, Machine-learning, Risks assessments, Risk assessment
National Category
Information Systems
Research subject Health and Caring Sciences, Health Informatics
Identifiers URN: urn:nbn:se:lnu:diva-122911 Scopus ID: 2-s2.0-85144202164 OAI: oai:DiVA.org:lnu-122911 DiVA, id: diva2:1776895
Conference 5th International Conference on Informatics and Data-Driven Medicine, IDDM 2022, 18-20 November 2022
2023-06-282023-06-282023-08-18 Bibliographically approved