Reducing Annotation Effort in Patient-Ventilator Asynchrony Detection With Distance-Based Clustering

Objective: This study aims to reduce expert annotation effort in detecting patient–ventilator asynchrony (PVA) by introducing a semi-supervised learning framework for time series classification. Methods and procedures: We propose a model-independent framework that integrates hierarchical clus...

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Bibliografiske detaljer

Principais autores:	Lars van de Kamp, Dolf Weller, Rick Thijssen, Bram Hunnekens, Tom Bakkes, Simona Turco, Corstiaan den Uil, Tom Oomen, Nathan van de Wouw
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2026-01-01
Serier:	IEEE Open Journal of Control Systems
Fag:	Data selection label projection patient-ventilator asynchrony semi-supervised learning
Online adgang:	https://ieeexplore.ieee.org/document/11482846/
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