Roy van Mierlo

Emailr.r.m.v.mierlotuenl

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ACACIA: Advancing cardiac care through interpretable AI (TKI2112P08)
van Riel, N. A. W. (Project Manager) & van Mierlo, R. (Project member)
1/05/21 → 30/04/26
Project: Third tier

2 Conference contribution
2 Poster

Electrocardiogram Feature Extraction: A Quantitative Comparison of Signal Reconstruction Using Traditional and Autoencoder Methods
van Mierlo, R. R. M. (Corresponding author), Relouw, F. J. A. & van Riel, N. A. W., 2 Jan 2026, Efficient Medical Artificial Intelligence: First International Workshop, EMA4MICCAI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings. Chen, T., Wu, J., Yuan, K., Xing, X., Du, Y., Kim, J., Padoy, N., Ren, H., Navab, N. & Bai, L. (eds.). Cham: Springer, p. 31-40 10 p. (Lecture Notes in Computer Science (LNCS); vol. 16318).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Open Access
File
6 Downloads (Pure)
Reproducing and improving one-dimensional convolutional neural networks for arterial blood pressure-based cardiac output estimation
van Mierlo, R. R. M., Bouwman, R. A. & van Riel, N. A. W., 29 Jul 2024, 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA). Institute of Electrical and Electronics Engineers, 6 p. 10596819
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Open Access
File
1 Link opens in a new tab Citation (Scopus)

106 Downloads (Pure)
Combining mechanistic modeling and machine learning to model slow hemodynamic changes in ICU patients
van Mierlo, R. R. M. & van Riel, N. A. W., 26 Jan 2023.
Research output: Contribution to conference › Poster

Open Access
File

40 Downloads (Pure)
Predicting arterial parameters using Physics Informed Neural Networks for estimation of Hemodynamic Deterioration and related Complications in ICU patients
van Mierlo, R. R. M. & van Riel, N. A. W., 20 Jun 2022, p. 104. 1 p.
Research output: Contribution to conference › Poster

Open Access
File

426 Downloads (Pure)

Roy van Mierlo

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Collaborations and top research areas from the last five years

Dive into details

ACACIA: Advancing cardiac care through interpretable AI (TKI2112P08)

Electrocardiogram Feature Extraction: A Quantitative Comparison of Signal Reconstruction Using Traditional and Autoencoder Methods

Reproducing and improving one-dimensional convolutional neural networks for arterial blood pressure-based cardiac output estimation

Combining mechanistic modeling and machine learning to model slow hemodynamic changes in ICU patients

Predicting arterial parameters using Physics Informed Neural Networks for estimation of Hemodynamic Deterioration and related Complications in ICU patients

Roy van Mierlo

Fingerprint

Collaborations and top research areas from the last five years

Projects

ACACIA: Advancing cardiac care through interpretable AI (TKI2112P08)

Research output

Electrocardiogram Feature Extraction: A Quantitative Comparison of Signal Reconstruction Using Traditional and Autoencoder Methods

Reproducing and improving one-dimensional convolutional neural networks for arterial blood pressure-based cardiac output estimation

Combining mechanistic modeling and machine learning to model slow hemodynamic changes in ICU patients

Predicting arterial parameters using Physics Informed Neural Networks for estimation of Hemodynamic Deterioration and related Complications in ICU patients