Items where Author is "Kampaktsis, PN"

BOHORAN, T.A., KAMPAKTSIS, P.N., MCLAUGHLIN, L., LEB, J., MOUSTAKIDIS, S., MCCANN, G.P. and GIANNAKIDIS, A., 2024. Embracing uncertainty flexibility: harnessing a supervised tree kernel to empower ensemble modelling for 2D echocardiography-based prediction of right ventricular volume. In: W. OSTEN, ed., Proceedings of SPIE: Sixteenth International Conference on Machine Vision (ICMV 2023). Bellingham, Washington: SPIE. ISBN 9781510674622

BOHORAN, T.A., KAMPAKTSIS, P.N., MCCANN, G.P. and GIANNAKIDIS, A., 2024. Fast-tracking the deep residual network training for arrhythmia classification by leveraging the power of dynamical systems. In: 17th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS 2023) proceedings. IEEE. ISBN 9798350370928

KAMPAKTSIS, P.N., BOHORAN, T.A., LEBEHN, M., MCLAUGHLIN, L., LEB, J., LIU, Z., MOUSTAKIDIS, S., SIOURAS, A., SINGH, A., HAHN, R.T., MCCANN, G.P. and GIANNAKIDIS, A., 2024. An attention‐based deep learning method for right ventricular quantification using 2D echocardiography: feasibility and accuracy. Echocardiography, 41 (1): e15719. ISSN 0742-2822

KAMPAKTSIS, P.N. and GIANNAKIDIS, A., 2023. Can deep learning improve 2D echocardiographic RV assessment? First important steps. JACC: Cardiovascular Imaging, 16 (12), p. 1635. ISSN 1936-878X

BOHORAN, T.A., KAMPAKTSIS, P.N., MCLAUGHLIN, L., LEB, J., MOUSTAKIDIS, S., MCCANN, G.P. and GIANNAKIDIS, A., 2023. Right ventricular volume prediction by feature tokenizer transformer-based regression of 2D echocardiography small-scale tabular data. In: O. BERNARD, P. CLARYSSE, N. DUCHATEAU, J. OHAYON and M. VIALLON, eds., Functional imaging and modeling of the heart: 12th International Conference, FIMH 2023, Lyon, France, June 19–22, 2023, proceedings. Cham: Springer, pp. 292-300. ISBN 9783031353017