Výsledky vyhledávání - "Marco Mamprin"

Akademický článek

Multi-view 3D skin feature recognition and localization for patient tracking in spinal surgery applications

Autor: Francesca Manni, Marco Mamprin, Ronald Holthuizen, Caifeng Shan, Gustav Burström, Adrian Elmi-Terander, Erik Edström, Svitlana Zinger, Peter H. N. de With

Publikováno v: BioMedical Engineering OnLine, Vol 20, Iss 1, Pp 1-15 (2021)

Abstract Background Minimally invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgica

Externí odkaz: https://doaj.org/article/4f0d7c86642744cd8b70797b677e9816

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Akademický článek

Local and Distributed Machine Learning for Inter-hospital Data Utilization: An Application for TAVI Outcome Prediction

Autor: Ricardo R. Lopes, Marco Mamprin, Jo M. Zelis, Pim A. L. Tonino, Martijn S. van Mourik, Marije M. Vis, Svitlana Zinger, Bas A. J. M. de Mol, Peter H. N. de With, Henk A. Marquering

Publikováno v: Frontiers in Cardiovascular Medicine, Vol 8 (2021)

Background: Machine learning models have been developed for numerous medical prognostic purposes. These models are commonly developed using data from single centers or regional registries. Including data from multiple centers improves robustness and

Externí odkaz: https://doaj.org/article/da14c3b27e7547969392b4a11ffd1ef0

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Akademický článek

Machine Learning for Predicting Mortality in Transcatheter Aortic Valve Implantation: An Inter-Center Cross Validation Study

Autor: Marco Mamprin, Ricardo R. Lopes, Jo M. Zelis, Pim A. L. Tonino, Martijn S. van Mourik, Marije M. Vis, Svitlana Zinger, Bas A. J. M. de Mol, Peter H. N. de With

Publikováno v: Journal of Cardiovascular Development and Disease, Vol 8, Iss 6, p 65 (2021)

Current prognostic risk scores for transcatheter aortic valve implantation (TAVI) do not benefit yet from modern machine learning techniques, which can improve risk stratification of one-year mortality of patients before TAVI. Despite the advancement

Externí odkaz: https://doaj.org/article/f4802f47d76d42608699bcc9b3bcddb5

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Akademický článek

Decision Trees for Predicting Mortality in Transcatheter Aortic Valve Implantation

Autor: Marco Mamprin, Jo M. Zelis, Pim A. L. Tonino, Sveta Zinger, Peter H. N. de With

Publikováno v: Bioengineering, Vol 8, Iss 2, p 22 (2021)

Current prognostic risk scores in cardiac surgery do not benefit yet from machine learning (ML). This research aims to create a machine learning model to predict one-year mortality of a patient after transcatheter aortic valve implantation (TAVI). We

Externí odkaz: https://doaj.org/article/bc546231ead54eddb7ea2f249738fd30

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Identification of patients at risk of cardiac conduction diseases requiring a permanent pacemaker following TAVI procedure: a deep-learning approach on ECG signals

Autor: Marco Mamprin, Jo M. Zelis, Pim A.L. Tonino, Svitlana Zinger, Peter H.N. De With

Publikováno v: Proceedings of the 12th International Conference on Biomedical Engineering and Technology.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::49a9fb175918fc603eee7920a4df2ede
https://doi.org/10.1145/3535694.3535708

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Towards non-invasive patient tracking: optical image analysis for spine tracking during spinal surgery procedures

Autor: Francesca Manni, Erik Edstrom, Peter H.N. de With, Xin Liu, Ronald Holthuizen, Svitlana Zinger, Fons van der Sommen, Caifeng Shan, Marco Mamprin, Gustav Burstrom, Adrian Elmi-Terander

Publikováno v: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, 3909-3914
STARTPAGE=3909;ENDPAGE=3914;TITLE=2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
EMBC

Surgical navigation systems can enhance surgeon vision and form a reliable image-guided tool for complex interventions as spinal surgery. The main prerequisite is successful patient tracking which implies optimal motion compensation. Nowadays, optica

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72ff06abfe4e9e711e5e0fbdacaa4f39
https://pubmed.ncbi.nlm.nih.gov/31946727

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Gradient Boosting on Decision Trees for Mortality Prediction in Transcatheter Aortic Valve Implantation

Autor: Marco Mamprin, S. Zinger, P. H. N. de With, J. M. Zelis, P. A. L. Tonino

Publikováno v: ICBET 2020: Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology, 325-329
STARTPAGE=325;ENDPAGE=329;TITLE=ICBET 2020: Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology

Current prognostic risk scores in cardiac surgery are based on statistics and do not yet benefit from machine learning. Statistical predictors are not robust enough to correctly identify patients who would benefit from Transcatheter Aortic Valve Impl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d6f734177ee26cef9791babf4af5bba
http://arxiv.org/abs/2001.02431

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