Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences

Autor: Anastasiou, Andreas, Papanastasiou, Angelos

The extensive emergence of big data techniques has led to an increasing interest in the development of change-point detection algorithms that can perform well in a multivariate, possibly high-dimensional setting. In the current paper, we propose a ne

Externí odkaz: http://arxiv.org/abs/2211.06856

Stochastic Workflow Modeling in a Surgical Ward:Towards Simulating and Predicting Patient Flow

Autor: Back, Christoffer O., Manataki, Areti, Papanastasiou, Angelos, Harrison, Ewen

Publikováno v: Back, C O, Manataki, A, Papanastasiou, A & Harrison, E 2021, Stochastic Workflow Modeling in a Surgical Ward : Towards Simulating and Predicting Patient Flow . in X Ye, F Soares, E De Maria, P Gómez Vilda, F Cabitza, A Fred & H Gamboa (eds), Biomedical Engineering Systems and Technologies-13th International Joint Conference, BIOSTEC 2020, Revised Selected Papers . Springer, Communications in Computer and Information Science, vol. 1400 CCIS, pp. 565-591, 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020, Valetta, Malta, 24/02/2020 . https://doi.org/10.1007/978-3-030-72379-8_28

Intelligent systems play an increasingly central role in healthcare systems worldwide. Nonetheless, operational friction represents an obstacle to full utilization of scarce resources and improvement of service standards. In this paper we address the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2751::a9fc9f35d6d0a00fa3399379081b3e3c
https://curis.ku.dk/portal/da/publications/stochastic-workflow-modeling-in-a-surgical-ward(e948d6e1-96fb-433e-9d6c-5edefaeea6c5).html