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A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.

P. Siogkas, D. Pleouras, V. Tsakanikas, V. Potsika, K. Tsiouris, A. Sakellarios, E. Karamouzi, F. Lagiou, G. Charalampopoulos, G. Galyfos, F. Sigala, I. Koncar, and D. Fotiadis. EMBC, page 1-4. IEEE, (2023)

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Eukleides Sakellarios

Johannes Sakellarios

Antonis Tsiongas

Antonis Papapantoleon

Antonis Chanos

Other publications of authors with the same name

A new method for the 3D reconstruction of coronary bifurcations pre and post the angioplasty procedure using the QCA.I. Andrikos, A. Sakellarios, P. Siogkas, P. Tsompou, V. Kigka, L. Michalis, and D. Fotiadis. EMBC, page 5757-5760. IEEE, (2019)A Machine Learning Model for the Identification of High risk Carotid Atherosclerotic Plaques.V. Kigka, A. Sakellarios, M. Mantzaris, V. Tsakanikas, V. Potsika, D. Palombo, F. Montecucco, and D. Fotiadis. EMBC, page 2266-2269. IEEE, (2021)Machine Learning Models for Cardiovascular Disease Events Prediction.K. Tsarapatsani, A. Sakellarios, V. Pezoulas, V. Tsakanikas, M. Kleber, W. März, L. Michalis, and D. Fotiadis. EMBC, page 1066-1069. IEEE, (2022)A hybrid data harmonization workflow using word embeddings for the interlinking of heterogeneous cross-domain clinical data structures.V. Pezoulas, A. Sakellarios, M. Kleber, J. Bosch, S. der Laan, F. Lamers, T. Lehtimäki, W. März, and D. Fotiadis. BHI, page 1-4. IEEE, (2021)Validation study of a 3D-QCA coronary reconstruction method using a hybrid intravascular ultrasound and angiography reconstruction method and patient-specific Fractional Flow Reserve data.P. Siogkas, L. Athanasiou, A. Sakellarios, K. Stefanou, T. Exarchos, M. Papafaklis, K. Naka, O. Parodi, L. Michalis, and D. Fotiadis. EMBC, page 973-976. IEEE, (2015)Validation study of a novel method for the 3D reconstruction of coronary bifurcations.P. Tsompou, I. Andrikos, G. Karanasiou, A. Sakellarios, N. Tsigkas, V. Kigka, S. Kyriakidis, L. Michalis, and D. Fotiadis. EMBC, page 1576-1579. IEEE, (2020)Site specific prediction of PCI stenting based on imaging and biomechanics data using gradient boosting tree ensembles.V. Kigka, A. Sakellarios, E. Georga, P. Siogkas, P. Tsompou, S. Kyriakidis, S. Rocchiccioli, G. Pelosi, K. Naka, L. Michalis and 1 other author(s). EMBC, page 2812-2815. IEEE, (2020)Numerical simulation of human hearing system.V. Isailovic, M. Nikolic, T. Bibas, A. Sakellarios, N. Tachos, M. Milosevic, and N. Filipovic. EAI Endorsed Trans. Pervasive Health Technol., 4 (13): e3 (2018)Investigation of crimping effects on the stent deployment through in silico modeling.V. Loukas, G. Karanasiou, D. Pleouras, C. Katsouras, N. Tachos, A. Sakellarios, A. Semertzioglou, L. Michalis, and D. Fotiadis. EMBC, page 621-624. IEEE, (2022)An in silico trials platform for the evaluation of effect of the arterial anatomy configuration on stent implantation*.G. Karanasiou, P. Tsompou, N. Tachos, G. Karanasiou, A. Sakellarios, S. Kyriakidis, L. Antonini, G. Pennati, L. Petrini, F. Gijsen and 4 other author(s). EMBC, page 4213-4217. IEEE, (2021)

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Disambiguation of "Sakellarios, Antonis I."

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DOI
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A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.

Please choose a person to relate this publication to

Eukleides Sakellarios

Johannes Sakellarios

Antonis Tsiongas

Antonis Papapantoleon

Antonis Chanos

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Sakellarios, Antonis I."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.

Please choose a person to relate this publication to

Eukleides Sakellarios

Johannes Sakellarios

Antonis Tsiongas

Antonis Papapantoleon

Antonis Chanos

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

A Machine Learning Model for the prediction of the progression of carotid arterial stenoses.