Doctoral Candidate
Anouk van Diepen
Department
Electrical Engineering
RESEARCH PROFILE
Anouk van Diepen (1992) received her MSc in Electrical Engineering at the Eindhoven University of Technology (TU/e) in 2017. She graduated within the BiasLab group in the Signal Processing Systems (SPS) group under the supervision of A. (Bert) de Vries. Currently, she is doctoral candidate at the Biomedical Diagnostics Lab, and works on improving invasive mechanical ventilation using model-based methods and machine learning techniques.
My dream is to use machine learning and smart algorithms to solve problems in health care.
Recent Publications
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Tom Bakkes,Anouk van Diepen,Ashley De Bie,Leon Montenij,Francesco Mojoli,Arthur Bouwman,Massimo Mischi,Pierre Woerlee,Simona Turco
Automated detection and classification of patient–ventilator asynchrony by means of machine learning and simulated data
Computer Methods and Programs in Biomedicine (2023) -
Anouk van Diepen,T.H.G.F. Bakkes,A.J.R. de Bie,S. Turco,R.A. Bouwman,P.H. Woerlee,M. Mischi
Evaluation of the accuracy of established patient inspiratory effort estimation methods during mechanical support ventilation
Heliyon (2023) -
Anouk van Diepen,Tom H.G.F. Bakkes,Ashley de Bie,Simona Turco,R. Arthur Bouwman,Pierre H. Woerlee,Massimo Mischi
A model-based approach to generating annotated pressure support waveforms
Journal of Clinical Monitoring and Computing (2022) -
A. van Diepen,T.H.G.F. Bakkes,A.J.R. de Bie,S. Turco,R.A. Bouwman,P.H. Woerlee,M. Mischi
A Model-based Approach to Generating Annotated Pressure Support Waveforms
43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021<br/> (2021) -
A. van Diepen,T.H.G.F. Bakkes,A.J.R. de Bie,S. Turco,R.A. Bouwman,P.H. Woerlee,M. Mischi
A Model-Based Approach to Synthetic Data Set Generation for Patient-Ventilator Waveforms for Machine Learning and Educational Use
arXiv (2021)
Ancillary Activities
No ancillary activities