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Evidence-based clinical engineering : machine learning algorithms for prediction of defibrillator performance

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Badnjević, Almir, Gurbeta Pokvić, Lejla, Hasičić, Mehrija, Bandić, Lejla, Mašetić, Zerina, Kovačević, Živorad, Kevrić, Jasmin and Pecchia, Leandro (2019) Evidence-based clinical engineering : machine learning algorithms for prediction of defibrillator performance. Biomedical Signal Processing and Control, 54 . 101629. doi:10.1016/j.bspc.2019.101629

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Official URL: https://doi.org/10.1016/j.bspc.2019.101629

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Abstract

Poorly regulated and insufficiently supervised medical devices (MDs) carry high risk of performance accuracy and safety deviations effecting the clinical accuracy and efficiency of patient diagnosis and treatments. Even with the increase of technological sophistication of devices, incidents involving defibrillator malfunction are unfortunately not rare.
To address this, we have developed an automated system based on machine learning algorithms that can predict performance of defibrillators and possible performance failures of the device which can affect performance. To develop an automated system, with high accuracy, overall dataset containing safety and performance measurements data was acquired from periodical safety and performance inspections of 1221 defibrillator. These inspections were carried out in period 2015–2017 in private and public healthcare institutions in Bosnia and Herzegovina by ISO 17,020 accredited laboratory. Out of overall number of samples, 974 of them were used during system development and 247 samples were used for subsequent validation of system performance. During system development, 5 different machine learning algorithms were used, and resulting systems were compared by obtained performance.

Item Type: Journal Article
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Science > Engineering
SWORD Depositor: Library Publications Router
Library of Congress Subject Headings (LCSH): Medical instruments and apparatus, Biomedical engineering, Machine learning, Evidence-based medicine -- Data processing, Medical electronics, Defibrillators
Journal or Publication Title: Biomedical Signal Processing and Control
Publisher: Elsevier
ISSN: 1746-8094
Official Date: September 2019
Dates:
DateEvent
September 2019Published
9 August 2019Available
22 July 2019Accepted
Volume: 54
Article Number: 101629
DOI: 10.1016/j.bspc.2019.101629
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

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