Anouk van Diepen
Contacta.v.diepen@ tue.nl Flux 5.084
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.
Automated detection and classification of patient–ventilator asynchrony by means of machine learning and simulated dataComputer Methods and Programs in Biomedicine (2023)
Evaluation of the accuracy of established patient inspiratory effort estimation methods during mechanical support ventilationHeliyon (2023)
A model-based approach to generating annotated pressure support waveformsJournal of Clinical Monitoring and Computing (2022)
A Model-based Approach to Generating Annotated Pressure Support Waveforms43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021<br/> (2021)
A Model-Based Approach to Synthetic Data Set Generation for Patient-Ventilator Waveforms for Machine Learning and Educational UsearXiv (2021)
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